Refresh papers and define Agent evaluation

papers/items/2026-2607-06624-agentlens-production-assessed-trajectory-reviews-for-coding-agent-evaluation.md

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+# Paper: AgentLens: Production-Assessed Trajectory Reviews for Coding Agent Evaluation
+
+---
+type: paper
+title: "AgentLens: Production-Assessed Trajectory Reviews for Coding Agent Evaluation"
+authors: Andrey Podivilov, Vadim Lomshakov, Sergey Savin, Matvei Startsev, Roman Pozharskiy, Maksim Parshin, Sergey Nikolenko
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.06624
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-14
+updated_at: 2026-07-14
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - planning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 19
+collection_queries: agent-evaluation, coding-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agent-evaluation, coding-agent
+- inferred topics: agent-evaluation, coding-agent, planning, tool-use
+- arXiv categories: cs.AI
+- collection score: 19
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.06624

papers/items/2026-2607-07405-reason-less-verify-more-deterministic-gates-recover-a-silent-policy-violation-fa.md

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+# Paper: Reason Less, Verify More: Deterministic Gates Recover a Silent Policy-Violation Failure Mode in Tool-Using LLM Agents
+
+---
+type: paper
+title: "Reason Less, Verify More: Deterministic Gates Recover a Silent Policy-Violation Failure Mode in Tool-Using LLM Agents"
+authors: Vikas Reddy, Sumanth Reddy Challaram, Abhishek Basu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.07405
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-11
+updated_at: 2026-07-11
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: tool-use
+- inferred topics: agent-evaluation, reasoning, tool-use
+- arXiv categories: cs.AI
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.07405

papers/items/2026-2607-08180-out-of-sight-compression-aware-content-protection-against-agentic-crawlers.md

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+# Paper: Out of Sight: Compression-Aware Content Protection against Agentic Crawlers
+
+---
+type: paper
+title: "Out of Sight: Compression-Aware Content Protection against Agentic Crawlers"
+authors: Xuefei Wang
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.08180
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-09
+updated_at: 2026-07-09
+status: queued
+relevance: high
+topics:
+  - computer-use
+  - memory
+  - reasoning
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CR
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: agentic-ai
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agentic-ai
+- inferred topics: computer-use, memory, reasoning, workflow-agent
+- arXiv categories: cs.CR
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.08180

papers/items/2026-2607-08282-multi-agent-firewall-architecture-for-privacy-protection-of-sensitive-data-in-in.md

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+# Paper: Multi-Agent Firewall Architecture for Privacy Protection of Sensitive Data in Interactions with Language Models
+
+---
+type: paper
+title: Multi-Agent Firewall Architecture for Privacy Protection of Sensitive Data in Interactions with Language Models
+authors: Hugo García Cuesta, Pablo Mateo Torrejón, Alfonso Sánchez-Macián
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.08282
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-09
+updated_at: 2026-07-09
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - computer-use
+  - multi-agent
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CR
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 17
+collection_queries: multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm
+- inferred topics: agent-evaluation, agent-safety, computer-use, multi-agent, tool-use, workflow-agent
+- arXiv categories: cs.CR
+- collection score: 17
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.08282

papers/items/2026-2607-08448-harness-vla-steering-frozen-vlas-into-reliable-manipulation-primitives-via-memor.md

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+# Paper: Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents
+
+---
+type: paper
+title: "Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents"
+authors: Yixian Zhang, Huanming Zhang, Feng Gao, Xiao Li, Zhihao Liu, Chunyang Zhu, Jiaxing Qiu, Yuchen Yan, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.08448
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-15
+updated_at: 2026-07-15
+status: queued
+relevance: high
+topics:
+  - coding-agent
+  - computer-use
+  - embodied-agent
+  - memory
+  - planning
+  - rag
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.RO
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 20
+collection_queries: coding-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: coding-agent
+- inferred topics: coding-agent, computer-use, embodied-agent, memory, planning, rag, reasoning, tool-use
+- arXiv categories: cs.RO
+- collection score: 20
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.08448

papers/items/2026-2607-08681-solarchain-eval-a-physics-constrained-benchmark-for-trustworthy-economic-agents-.md

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+# Paper: SolarChain-Eval: A Physics-Constrained Benchmark for Trustworthy Economic Agents in Decentralized Energy Markets
+
+---
+type: paper
+title: "SolarChain-Eval: A Physics-Constrained Benchmark for Trustworthy Economic Agents in Decentralized Energy Markets"
+authors: Shilin Ou, Yifan Xu, Luyao Zhang
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.08681
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-09
+updated_at: 2026-07-09
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - planning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 18
+collection_queries: agent-evaluation, agentic-ai, autonomous-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agent-evaluation, agentic-ai, autonomous-agent-llm
+- inferred topics: agent-evaluation, agent-safety, planning, tool-use
+- arXiv categories: cs.AI
+- collection score: 18
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.08681

papers/items/2026-2607-08716-remember-when-it-matters-proactive-memory-agent-for-long-horizon-agents.md

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+# Paper: Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents
+
+---
+type: paper
+title: "Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents"
+authors: Yifan Wu, Lizhu Zhang, Yuhang Zhou, Mingyi Wang, Bo Peng, Serena Li, Xiangjun Fan, Zhuokai Zhao
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.08716
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-09
+updated_at: 2026-07-09
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+  - memory
+  - planning
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: agent-memory
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agent-memory
+- inferred topics: agent-evaluation, computer-use, memory, planning, rag, tool-use
+- arXiv categories: cs.AI
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.08716

papers/items/2026-2607-08894-gats-graph-augmented-tree-search-with-layered-world-models-for-efficient-agent-p.md

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+# Paper: GATS: Graph-Augmented Tree Search with Layered World Models for Efficient Agent Planning
+
+---
+type: paper
+title: "GATS: Graph-Augmented Tree Search with Layered World Models for Efficient Agent Planning"
+authors: Maureese Williams, Dymitr Nowicki
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.08894
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-09
+updated_at: 2026-07-09
+status: queued
+relevance: high
+topics:
+  - coding-agent
+  - computer-use
+  - embodied-agent
+  - planning
+  - tool-use
+  - workflow-agent
+  - world-model
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 16
+collection_queries: language-agent, planning-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: language-agent, planning-agent
+- inferred topics: coding-agent, computer-use, embodied-agent, planning, tool-use, workflow-agent, world-model
+- arXiv categories: cs.AI
+- collection score: 16
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.08894

papers/items/2026-2607-08960-eluna-an-agentic-llm-system-for-automating-warehouse-operations-with-reasoning-a.md

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+# Paper: Eluna: An Agentic LLM System for Automating Warehouse Operations with Reasoning and Task Execution
+
+---
+type: paper
+title: "Eluna: An Agentic LLM System for Automating Warehouse Operations with Reasoning and Task Execution"
+authors: Ning Liu, Kalle Kujanpää, Zhaoxuan Zhu, P Aditya Sreekar, Kaiwen Liu, Chuanneng Sun, Jorge Marchena Menendez, Matthew Bales, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.08960
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-09
+updated_at: 2026-07-09
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+  - memory
+  - multi-agent
+  - reasoning
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.LG
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 19
+collection_queries: multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm
+- inferred topics: agent-evaluation, computer-use, memory, multi-agent, reasoning
+- arXiv categories: cs.LG
+- collection score: 19
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.08960

papers/items/2026-2607-08983-scate-learning-to-supervise-coding-agents-for-cost-effective-test-generation.md

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+# Paper: SCATE: Learning to Supervise Coding Agents for Cost-Effective Test Generation
+
+---
+type: paper
+title: "SCATE: Learning to Supervise Coding Agents for Cost-Effective Test Generation"
+authors: Sijia Gu, Noor Nashid, Ali Mesbah
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.08983
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-09
+updated_at: 2026-07-09
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.SE
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: coding-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: coding-agent
+- inferred topics: agent-evaluation, coding-agent, rag, tool-use
+- arXiv categories: cs.SE
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.08983

papers/items/2026-2607-09076-neuro-agentic-control-a-deep-learning-based-llm-powered-agentic-ai-framework-for.md

@@ -0,0 +1,62 @@
+# Paper: Neuro-Agentic Control: A Deep Learning-based LLM-Powered Agentic AI Framework for Controlling Security Controls
+
+---
+type: paper
+title: "Neuro-Agentic Control: A Deep Learning-based LLM-Powered Agentic AI Framework for Controlling Security Controls"
+authors: Saroj Gopali, Bipin Chhetri, Deepika Giri, Sima Siami-Namini, Akbar Siami Namin
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.09076
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-09
+updated_at: 2026-07-09
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - planning
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: agentic-ai
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agentic-ai
+- inferred topics: agent-evaluation, agent-safety, planning, reasoning, tool-use
+- arXiv categories: cs.AI
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.09076

papers/items/2026-2607-09092-agentkgv-agentic-llm-rag-framework-with-two-stage-training-for-the-fact-verifica.md

@@ -0,0 +1,61 @@
+# Paper: AgentKGV: Agentic LLM-RAG Framework with Two-Stage Training for the Fact Verification of Knowledge Graphs
+
+---
+type: paper
+title: "AgentKGV: Agentic LLM-RAG Framework with Two-Stage Training for the Fact Verification of Knowledge Graphs"
+authors: Yumin Heo, Hyeon-gu Lee, Sumin Seo, Youngjoong Ko
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.09092
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-10
+updated_at: 2026-07-10
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - rag
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CL
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: rag-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: rag-agent
+- inferred topics: agent-evaluation, rag, reasoning, tool-use
+- arXiv categories: cs.CL
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.09092

papers/items/2026-2607-09101-multi-agent-llm-collaboration-for-unit-test-generation-via-human-testing-inspire.md

@@ -0,0 +1,65 @@
+# Paper: Multi-Agent LLM Collaboration for Unit Test Generation via Human-Testing-Inspired Workflows
+
+---
+type: paper
+title: Multi-Agent LLM Collaboration for Unit Test Generation via Human-Testing-Inspired Workflows
+authors: Quanjun Zhang, Ye Shang, Siqi Gu, Jianyi Zhou, Chunrong Fang, Zhenyu Chen, Liang Xiao
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.09101
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-10
+updated_at: 2026-07-10
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - multi-agent
+  - planning
+  - rag
+  - reasoning
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.SE
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 18
+collection_queries: multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm
+- inferred topics: agent-evaluation, coding-agent, multi-agent, planning, rag, reasoning, tool-use, workflow-agent
+- arXiv categories: cs.SE
+- collection score: 18
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.09101

papers/items/2026-2607-09153-kv-prm-efficient-process-reward-modeling-via-kv-cache-transfer-for-multi-agent-t.md

@@ -0,0 +1,62 @@
+# Paper: KV-PRM: Efficient Process Reward Modeling via KV-Cache Transfer for Multi-Agent Test-Time Scaling
+
+---
+type: paper
+title: "KV-PRM: Efficient Process Reward Modeling via KV-Cache Transfer for Multi-Agent Test-Time Scaling"
+authors: Peng Kuang, Haibo Jin, Xiaoyu Han, Yanli Wang, Xiaopeng Yuan, Ye Yu, Kaidi Xu, Haohan Wang
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.09153
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-10
+updated_at: 2026-07-10
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - computer-use
+  - memory
+  - multi-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 17
+collection_queries: multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm
+- inferred topics: agent-evaluation, coding-agent, computer-use, memory, multi-agent
+- arXiv categories: cs.AI
+- collection score: 17
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.09153

papers/items/2026-2607-09179-malaika-understanding-malware-through-tri-grounded-agentic-reasoning.md

@@ -0,0 +1,63 @@
+# Paper: Malaika: Understanding Malware through Tri-Grounded Agentic Reasoning
+
+---
+type: paper
+title: "Malaika: Understanding Malware through Tri-Grounded Agentic Reasoning"
+authors: Xingzhi Qian, Xinran Zheng, Yiling He, Lorenzo Cavallaro
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.09179
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-10
+updated_at: 2026-07-10
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - multi-agent
+  - rag
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CR
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 17
+collection_queries: multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm
+- inferred topics: agent-evaluation, agent-safety, multi-agent, rag, reasoning, tool-use
+- arXiv categories: cs.CR
+- collection score: 17
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.09179

papers/items/2026-2607-09195-toward-auditable-ai-scientists-a-hypothesis-evolution-protocol-for-llm-agents.md

@@ -0,0 +1,61 @@
+# Paper: Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents
+
+---
+type: paper
+title: "Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents"
+authors: Izumi Takahara, Teruyasu Mizoguchi
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.09195
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-10
+updated_at: 2026-07-10
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - planning
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 17
+collection_queries: planning-agent, tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: planning-agent, tool-use
+- inferred topics: agent-evaluation, planning, reasoning, tool-use
+- arXiv categories: cs.AI
+- collection score: 17
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.09195

papers/items/2026-2607-09553-writing-bug-reports-for-software-repair-agents-what-information-matters-most.md

@@ -0,0 +1,60 @@
+# Paper: Writing Bug Reports for Software Repair Agents: What Information Matters Most?
+
+---
+type: paper
+title: "Writing Bug Reports for Software Repair Agents: What Information Matters Most?"
+authors: Vincenzo Luigi Bruno, Alessandro Giagnorio, Daniele Bifolco, Leon Wienges, Massimiliano Di Penta, Gabriele Bavota
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.09553
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-10
+updated_at: 2026-07-10
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.SE
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: coding-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: coding-agent
+- inferred topics: agent-evaluation, coding-agent, workflow-agent
+- arXiv categories: cs.SE
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.09553

papers/items/2026-2607-09653-vexaiot-autonomous-iot-vulnerability-exploitation-using-ai-agents.md

@@ -0,0 +1,65 @@
+# Paper: VEXAIoT: Autonomous IoT Vulnerability EXploitation using AI Agents
+
+---
+type: paper
+title: "VEXAIoT: Autonomous IoT Vulnerability EXploitation using AI Agents"
+authors: Katherine Swinea, Kshitiz Aryal, Lopamudra Praharaj, Maanak Gupta
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.09653
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-10
+updated_at: 2026-07-10
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - multi-agent
+  - planning
+  - rag
+  - reasoning
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CR
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 20
+collection_queries: multi-agent-llm, planning-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm, planning-agent
+- inferred topics: agent-evaluation, agent-safety, multi-agent, planning, rag, reasoning, tool-use, workflow-agent
+- arXiv categories: cs.CR
+- collection score: 20
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.09653

papers/items/2026-2607-09902-do-these-violent-delights-have-violent-ends-measuring-the-post-merge-fate-of-age.md

@@ -0,0 +1,62 @@
+# Paper: Do These Violent Delights Have Violent Ends? Measuring the Post-Merge Fate of Agentic Code
+
+---
+type: paper
+title: Do These Violent Delights Have Violent Ends? Measuring the Post-Merge Fate of Agentic Code
+authors: Chunqiu Steven Xia, Courtney Miller
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.09902
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-10
+updated_at: 2026-07-10
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - coding-agent
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.SE
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: coding-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: coding-agent
+- inferred topics: agent-evaluation, agent-safety, coding-agent, rag, tool-use
+- arXiv categories: cs.SE
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.09902

papers/items/2026-2607-09996-who-when-pro-can-llms-really-attribute-failures-in-ai-agents.md

@@ -0,0 +1,59 @@
+# Paper: Who&When Pro: Can LLMs Really Attribute Failures in AI Agents?
+
+---
+type: paper
+title: "Who&When Pro: Can LLMs Really Attribute Failures in AI Agents?"
+authors: Jiale Liu, Huajun Xi, Shaokun Zhang, Yifan Zeng, Tianwei Yue, Chi Wang, Jian Kang, Qingyun Wu, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.09996
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-10
+updated_at: 2026-07-10
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: ai-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: ai-agent
+- inferred topics: agent-evaluation, computer-use
+- arXiv categories: cs.AI
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.09996

papers/items/2026-2607-10057-quantum-circuit-vision-cost-aware-evaluation-of-visual-ai-agents-for-quantum-cod.md

@@ -0,0 +1,59 @@
+# Paper: Quantum Circuit Vision: Cost-Aware Evaluation of Visual AI Agents for Quantum Code Generation
+
+---
+type: paper
+title: "Quantum Circuit Vision: Cost-Aware Evaluation of Visual AI Agents for Quantum Code Generation"
+authors: Dongping Liu, Aoyu Zhang, Luyao Zhang
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.10057
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-10
+updated_at: 2026-07-10
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - reasoning
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - quant-ph
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: ai-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: ai-agent
+- inferred topics: agent-evaluation, reasoning
+- arXiv categories: quant-ph
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.10057

papers/items/2026-2607-10265-tgms-an-agent-native-bi-temporal-graph-management-system.md

@@ -0,0 +1,62 @@
+# Paper: TGMS: An Agent-Native Bi-Temporal Graph Management System
+
+---
+type: paper
+title: "TGMS: An Agent-Native Bi-Temporal Graph Management System"
+authors: Xiaofei Zhang
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.10265
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-11
+updated_at: 2026-07-11
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - planning
+  - rag
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.DB
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: planning-agent, rag-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: planning-agent, rag-agent
+- inferred topics: agent-evaluation, planning, rag, reasoning, tool-use
+- arXiv categories: cs.DB
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.10265

papers/items/2026-2607-10286-can-agentic-trading-systems-pay-for-their-own-intelligence.md

@@ -0,0 +1,60 @@
+# Paper: Can Agentic Trading Systems Pay for Their Own Intelligence?
+
+---
+type: paper
+title: Can Agentic Trading Systems Pay for Their Own Intelligence?
+authors: Qiqi Duan, Changlun Li, Chen Wang, Fan Zhang, Mengxiang Wang, Dayi Miao, Peixian Ma, Jiangpeng Yan, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.10286
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-11
+updated_at: 2026-07-11
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: tool-use
+- inferred topics: agent-evaluation, reasoning, tool-use
+- arXiv categories: cs.AI
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.10286

papers/items/2026-2607-10463-grasp-granularity-aware-search-policy-for-agentic-rag.md

@@ -0,0 +1,61 @@
+# Paper: GRASP: GRanularity-Aware Search Policy for Agentic RAG
+
+---
+type: paper
+title: "GRASP: GRanularity-Aware Search Policy for Agentic RAG"
+authors: Varun Gandhi, Jaewook Lee, Shantanu Todmal, Franck Dernoncourt, Ryan Rossi, Zichao Wang, Andrew Lan
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.10463
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-11
+updated_at: 2026-07-11
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - rag
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: rag-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: rag-agent
+- inferred topics: agent-evaluation, rag, reasoning, tool-use
+- arXiv categories: cs.AI
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.10463

papers/items/2026-2607-10490-netinjectbench-benchmarking-indirect-prompt-injection-in-tool-using-large-langua.md

@@ -0,0 +1,60 @@
+# Paper: NetInjectBench: Benchmarking Indirect Prompt Injection in Tool-Using Large Language Model Agents for Network Operations
+
+---
+type: paper
+title: "NetInjectBench: Benchmarking Indirect Prompt Injection in Tool-Using Large Language Model Agents for Network Operations"
+authors: Ruksat Khan Shayoni, Muhammad Faraz Shoaib, S M Asif Hossain, M. F. Mridha
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.10490
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-11
+updated_at: 2026-07-11
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CR
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: tool-use
+- inferred topics: agent-evaluation, agent-safety, tool-use
+- arXiv categories: cs.CR
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.10490

papers/items/2026-2607-10582-memdecay-region-aware-kv-cache-eviction-for-efficient-llm-agent-inference.md

@@ -0,0 +1,63 @@
+# Paper: MemDecay: Region-Aware KV Cache Eviction for Efficient LLM Agent Inference
+
+---
+type: paper
+title: "MemDecay: Region-Aware KV Cache Eviction for Efficient LLM Agent Inference"
+authors: Venkatesha Matam, Keon Kim
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.10582
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-12
+updated_at: 2026-07-12
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - memory
+  - planning
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.LG
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 17
+collection_queries: planning-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: planning-agent
+- inferred topics: agent-evaluation, coding-agent, memory, planning, reasoning, tool-use
+- arXiv categories: cs.LG
+- collection score: 17
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.10582

papers/items/2026-2607-10608-the-compliance-trap-diagnosing-how-ai-agents-consume-conflicting-memory.md

@@ -0,0 +1,63 @@
+# Paper: The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory
+
+---
+type: paper
+title: "The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory"
+authors: Yixiong Chen, Xinyi Bai, Alan Yuille
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.10608
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-12
+updated_at: 2026-07-12
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+  - memory
+  - planning
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 18
+collection_queries: ai-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: ai-agent
+- inferred topics: agent-evaluation, computer-use, memory, planning, rag, tool-use
+- arXiv categories: cs.AI
+- collection score: 18
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.10608

papers/items/2026-2607-10789-imaging-101-benchmarking-llm-coding-agents-on-scientific-computational-imaging.md

@@ -0,0 +1,60 @@
+# Paper: Imaging-101: Benchmarking LLM Coding Agents on Scientific Computational Imaging
+
+---
+type: paper
+title: "Imaging-101: Benchmarking LLM Coding Agents on Scientific Computational Imaging"
+authors: Siyi Chen, Jiahe Ying, Yixuan Jia, Yuxuan Gu, Enze Ye, Weimin Bai, Zhijun Zeng, Shaochi Ren, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.10789
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-12
+updated_at: 2026-07-12
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - planning
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 17
+collection_queries: coding-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: coding-agent
+- inferred topics: agent-evaluation, coding-agent, planning
+- arXiv categories: cs.AI
+- collection score: 17
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.10789

papers/items/2026-2607-10994-a-multi-agent-framework-for-zero-dimensional-reduced-order-model-planning.md

@@ -0,0 +1,66 @@
+# Paper: A Multi-Agent Framework for Zero-Dimensional Reduced-Order Model Planning
+
+---
+type: paper
+title: A Multi-Agent Framework for Zero-Dimensional Reduced-Order Model Planning
+authors: Bingteng Sun, Hao Yin, Yiling Chen, Renjie Xiao, Lei Xie, Shanyou Wang, Ruonan Wang, Shubao Chen, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.10994
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-12
+updated_at: 2026-07-12
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+  - embodied-agent
+  - multi-agent
+  - planning
+  - rag
+  - reasoning
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.LG
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 22
+collection_queries: multi-agent-llm, planning-agent, rag-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm, planning-agent, rag-agent
+- inferred topics: agent-evaluation, computer-use, embodied-agent, multi-agent, planning, rag, reasoning, tool-use, workflow-agent
+- arXiv categories: cs.LG
+- collection score: 22
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.10994

papers/items/2026-2607-11042-backendforge-benchmarking-agentic-end-to-end-code-generation-with-backend-servic.md

@@ -0,0 +1,60 @@
+# Paper: BackendForge: Benchmarking Agentic End-to-End Code Generation with Backend Services
+
+---
+type: paper
+title: "BackendForge: Benchmarking Agentic End-to-End Code Generation with Backend Services"
+authors: Yuzhe Guo, Mengzhou Wu, Yuan Cao, Jialei Wei, Dezhi Ran, Wei Yang, Tao Xie
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.11042
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-12
+updated_at: 2026-07-12
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.SE
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 17
+collection_queries: coding-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: coding-agent
+- inferred topics: agent-evaluation, coding-agent, tool-use
+- arXiv categories: cs.SE
+- collection score: 17
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.11042

papers/items/2026-2607-11046-retrieval-oriented-code-representations-in-agentic-bug-localization.md

@@ -0,0 +1,61 @@
+# Paper: Retrieval-Oriented Code Representations in Agentic Bug Localization
+
+---
+type: paper
+title: Retrieval-Oriented Code Representations in Agentic Bug Localization
+authors: Genevieve Caumartin, Tse-Hsun, Chen, Diego Elias Costa
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.11046
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-12
+updated_at: 2026-07-12
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - computer-use
+  - rag
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.SE
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: coding-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: coding-agent
+- inferred topics: agent-evaluation, coding-agent, computer-use, rag
+- arXiv categories: cs.SE
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.11046

papers/items/2026-2607-11119-via-visual-interface-agent-for-robot-control.md

@@ -0,0 +1,64 @@
+# Paper: VIA: Visual Interface Agent for Robot Control
+
+---
+type: paper
+title: "VIA: Visual Interface Agent for Robot Control"
+authors: Hengyuan Hu, Priya Sundaresan, Jensen Gao, Dorsa Sadigh
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.11119
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - coding-agent
+  - computer-use
+  - embodied-agent
+  - planning
+  - rag
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.RO
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: web-gui-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: web-gui-agent
+- inferred topics: coding-agent, computer-use, embodied-agent, planning, rag, reasoning, tool-use
+- arXiv categories: cs.RO
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.11119

papers/items/2026-2607-11126-toolatlas-learning-once-reusing-everywhere-with-tool-side-memory.md

@@ -0,0 +1,61 @@
+# Paper: ToolAtlas: Learning Once, Reusing Everywhere with Tool-Side Memory
+
+---
+type: paper
+title: "ToolAtlas: Learning Once, Reusing Everywhere with Tool-Side Memory"
+authors: Yue Fang, Zhibang Yang, Fangkai Yang, Xiaoting Qin, Liqun Li, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.11126
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+  - memory
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.LG
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: tool-use
+- inferred topics: agent-evaluation, computer-use, memory, tool-use
+- arXiv categories: cs.LG
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.11126

papers/items/2026-2607-11141-nextfund-a-unified-performance-tracking-platform-for-agentic-portfolio-managemen.md

@@ -0,0 +1,61 @@
+# Paper: NextFund: A Unified Performance Tracking Platform for Agentic Portfolio Management
+
+---
+type: paper
+title: "NextFund: A Unified Performance Tracking Platform for Agentic Portfolio Management"
+authors: Changlun Li, Peixian Ma, Qiqi Duan, Zhenyu Lin, Peineng Wu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.11141
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - multi-agent
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 17
+collection_queries: multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm
+- inferred topics: agent-evaluation, agent-safety, multi-agent, tool-use
+- arXiv categories: cs.AI
+- collection score: 17
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.11141

papers/items/2026-2607-11185-scalecua-scaling-computer-use-agents-with-verifiable-task-synthesis-and-efficien.md

@@ -0,0 +1,61 @@
+# Paper: SCALECUA: Scaling Computer Use Agents with Verifiable Task Synthesis and Efficient Online RL
+
+---
+type: paper
+title: "SCALECUA: Scaling Computer Use Agents with Verifiable Task Synthesis and Efficient Online RL"
+authors: Bowen Lv, Xiao Liu, Yanyu Ren, Hanyu Lai, Bohao Jing, Hanchen Zhang, Yanxiao Zhao, Shuntian Yao, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.11185
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - computer-use
+  - multi-agent
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: web-gui-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: web-gui-agent
+- inferred topics: computer-use, multi-agent, tool-use, workflow-agent
+- arXiv categories: cs.AI
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.11185

papers/items/2026-2607-11250-multi-agent-llms-fail-to-explore-each-other.md

@@ -0,0 +1,61 @@
+# Paper: Multi-Agent LLMs Fail to Explore Each Other
+
+---
+type: paper
+title: Multi-Agent LLMs Fail to Explore Each Other
+authors: Hyeong Kyu Choi, Jiatong Li, Wendi Li, Xin Eric Wang, Sharon Li
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.11250
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+  - multi-agent
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.MA
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm
+- inferred topics: agent-evaluation, computer-use, multi-agent, tool-use
+- arXiv categories: cs.MA
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.11250

papers/items/2026-2607-11388-structagent-harness-long-horizon-digital-agents-with-unified-causal-structure.md

@@ -0,0 +1,62 @@
+# Paper: StructAgent: Harness Long-horizon Digital Agents with Unified Causal Structure
+
+---
+type: paper
+title: "StructAgent: Harness Long-horizon Digital Agents with Unified Causal Structure"
+authors: Wenyi Wu, Sibo Zhu, Kun Zhou, Aayush Salvi, Zixuan Song, Biwei Huang
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.11388
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - computer-use
+  - planning
+  - reasoning
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: web-gui-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: web-gui-agent
+- inferred topics: computer-use, planning, reasoning, tool-use, workflow-agent
+- arXiv categories: cs.AI
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.11388

papers/items/2026-2607-11423-tofu-a-white-box-token-efficient-agent-harness-for-researchers.md

@@ -0,0 +1,61 @@
+# Paper: ToFu: A White-Box, Token-Efficient Agent Harness for Researchers
+
+---
+type: paper
+title: "ToFu: A White-Box, Token-Efficient Agent Harness for Researchers"
+authors: Junhao Ruan, Yuan Ge, Bei Li, Yongjing Yin, Yuchun Fan, Xin Chen, Jingang Wang, Chenglong Wang, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.11423
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CL
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: tool-use
+- inferred topics: agent-evaluation, coding-agent, tool-use, workflow-agent
+- arXiv categories: cs.CL
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.11423

papers/items/2026-2607-11444-umoe-unlocking-every-expert-in-domain-specific-training.md

@@ -0,0 +1,61 @@
+# Paper: UMoE:Unlocking Every Expert in Domain-Specific Training
+
+---
+type: paper
+title: "UMoE:Unlocking Every Expert in Domain-Specific Training"
+authors: Xuefeng Li, Pengfei Liu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.11444
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CL
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: coding-agent, tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: coding-agent, tool-use
+- inferred topics: agent-evaluation, coding-agent, rag, tool-use
+- arXiv categories: cs.CL
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.11444

papers/items/2026-2607-11565-heuristic-learning-for-active-flow-control-using-coding-agents.md

@@ -0,0 +1,61 @@
+# Paper: Heuristic Learning for Active Flow Control Using Coding Agents
+
+---
+type: paper
+title: Heuristic Learning for Active Flow Control Using Coding Agents
+authors: Paul Garnier, Jonathan Viquerat, Elie Hachem
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.11565
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - tool-use
+  - world-model
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.LG
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: coding-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: coding-agent
+- inferred topics: agent-evaluation, coding-agent, tool-use, world-model
+- arXiv categories: cs.LG
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.11565

papers/items/2026-2607-11751-when-local-monitors-miss-compositional-harm-diagnosing-distributed-backdoors-in-.md

@@ -0,0 +1,63 @@
+# Paper: When Local Monitors Miss Compositional Harm: Diagnosing Distributed Backdoors in Multi-Agent Systems
+
+---
+type: paper
+title: "When Local Monitors Miss Compositional Harm: Diagnosing Distributed Backdoors in Multi-Agent Systems"
+authors: Yibo Hu, Ren Wang
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.11751
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - coding-agent
+  - multi-agent
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CR
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 18
+collection_queries: multi-agent-llm, tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm, tool-use
+- inferred topics: agent-evaluation, agent-safety, coding-agent, multi-agent, rag, tool-use
+- arXiv categories: cs.CR
+- collection score: 18
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.11751

papers/items/2026-2607-12056-designing-agent-ready-websites-for-ai-web-agents-a-framework-for-machine-readabi.md

@@ -0,0 +1,62 @@
+# Paper: Designing Agent-Ready Websites for AI Web Agents: A Framework for Machine Readability, Actionability, and Decision Reliability
+
+---
+type: paper
+title: "Designing Agent-Ready Websites for AI Web Agents: A Framework for Machine Readability, Actionability, and Decision Reliability"
+authors: Said Elnaffar, Farzad Rashidi
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.12056
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+  - rag
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: ai-agent, web-gui-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: ai-agent, web-gui-agent
+- inferred topics: agent-evaluation, computer-use, rag, tool-use, workflow-agent
+- arXiv categories: cs.AI
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.12056

papers/items/2026-2607-12068-beyond-test-presence-assessing-the-quality-and-robustness-of-agent-generated-tes.md

@@ -0,0 +1,61 @@
+# Paper: Beyond Test Presence: Assessing the Quality and Robustness of Agent-Generated Tests in Open-Source Projects
+
+---
+type: paper
+title: "Beyond Test Presence: Assessing the Quality and Robustness of Agent-Generated Tests in Open-Source Projects"
+authors: Preet Jhanglani, Zeel Kaushal Desai, Vidhi Kansara, Eman Abdullah AlOmar
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.12068
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - coding-agent
+  - rag
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.SE
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: ai-agent, coding-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: ai-agent, coding-agent
+- inferred topics: agent-evaluation, agent-safety, coding-agent, rag
+- arXiv categories: cs.SE
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.12068

papers/items/2026-2607-12122-an-agentic-ai-scientific-community-for-automated-neural-operator-discovery.md

@@ -0,0 +1,60 @@
+# Paper: An Agentic AI Scientific Community for Automated Neural Operator Discovery
+
+---
+type: paper
+title: An Agentic AI Scientific Community for Automated Neural Operator Discovery
+authors: Luis Loo, Ulisses Braga-Neto
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.12122
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - planning
+  - world-model
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.LG
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: agentic-ai
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agentic-ai
+- inferred topics: agent-evaluation, planning, world-model
+- arXiv categories: cs.LG
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.12122

papers/items/2026-2607-12215-fine-tuned-multi-agent-framework-for-detecting-ocean-in-life-narratives.md

@@ -0,0 +1,60 @@
+# Paper: Fine-Tuned Multi-Agent Framework for Detecting OCEAN in Life Narratives
+
+---
+type: paper
+title: Fine-Tuned Multi-Agent Framework for Detecting OCEAN in Life Narratives
+authors: Rasiq Hussain, Darshil Italiya, Joshua Oltmanns, Mehak Gupta
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.12215
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - multi-agent
+  - reasoning
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CL
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm
+- inferred topics: agent-evaluation, multi-agent, reasoning
+- arXiv categories: cs.CL
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.12215

papers/items/2026-2607-12267-track-rank-crack-epistemic-working-memory-scales-multi-hop-reasoning-in-language.md

@@ -0,0 +1,62 @@
+# Paper: Track, Rank, Crack: Epistemic Working Memory Scales Multi-Hop Reasoning in Language Agents
+
+---
+type: paper
+title: "Track, Rank, Crack: Epistemic Working Memory Scales Multi-Hop Reasoning in Language Agents"
+authors: Ning Liu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.12267
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - memory
+  - rag
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.LG
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 19
+collection_queries: language-agent, tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: language-agent, tool-use
+- inferred topics: agent-evaluation, memory, rag, reasoning, tool-use
+- arXiv categories: cs.LG
+- collection score: 19
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.12267

papers/items/2026-2607-12397-critic-experience-bank-self-evolving-step-level-confidence-estimation-for-llm-ag.md

@@ -0,0 +1,60 @@
+# Paper: Critic Experience Bank: Self-Evolving Step-Level Confidence Estimation for LLM Agents
+
+---
+type: paper
+title: "Critic Experience Bank: Self-Evolving Step-Level Confidence Estimation for LLM Agents"
+authors: Yaopei Zeng, Congchao Wang, JianHang Chen, Nan Wang, Yurui Chang, Lu Lin
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.12397
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-14
+updated_at: 2026-07-14
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - memory
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: agent-evaluation
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agent-evaluation
+- inferred topics: agent-evaluation, memory, tool-use
+- arXiv categories: cs.AI
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.12397

papers/items/2026-2607-12406-isolation-as-a-first-class-principle-for-llm-agent-system-safety-concepts-taxono.md

@@ -0,0 +1,63 @@
+# Paper: Isolation as a First-Class Principle for LLM-Agent System Safety: Concepts, Taxonomy, Challenges and Future Directions
+
+---
+type: paper
+title: "Isolation as a First-Class Principle for LLM-Agent System Safety: Concepts, Taxonomy, Challenges and Future Directions"
+authors: Huihao Jing, Wenbin Hu, Shaojin Chen, Haochen Shi, Sirui Zhang, Hanyu Yang, Changxuan Fan, Zhongwei Xie, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.12406
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-14
+updated_at: 2026-07-14
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - memory
+  - rag
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 16
+collection_queries: agentic-ai
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agentic-ai
+- inferred topics: agent-evaluation, agent-safety, memory, rag, tool-use, workflow-agent
+- arXiv categories: cs.AI
+- collection score: 16
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.12406

papers/items/2026-2607-12463-function-aware-fill-in-the-middle-as-mid-training-for-coding-agent-foundation-mo.md

@@ -0,0 +1,61 @@
+# Paper: Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models
+
+---
+type: paper
+title: Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models
+authors: Yubo Wang, Jiarong Liang, Yuxuan Zhang, Xuye Liu, Cong Wei, Yuyu Zhang, Ping Nie, Wenhu Chen
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.12463
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-19
+updated_at: 2026-07-19
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 17
+collection_queries: coding-agent, function-calling, tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: coding-agent, function-calling, tool-use
+- inferred topics: agent-evaluation, coding-agent, reasoning, tool-use
+- arXiv categories: cs.AI
+- collection score: 17
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.12463

papers/items/2026-2607-13027-palmclaw-a-native-on-device-agent-framework-for-mobile-phones.md

@@ -0,0 +1,61 @@
+# Paper: PalmClaw: A Native On-Device Agent Framework for Mobile Phones
+
+---
+type: paper
+title: "PalmClaw: A Native On-Device Agent Framework for Mobile Phones"
+authors: Hongru Cai, Yongqi Li, Ran Wei, Wenjie Li
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.13027
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-14
+updated_at: 2026-07-14
+status: queued
+relevance: high
+topics:
+  - computer-use
+  - memory
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CL
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: tool-use
+- inferred topics: computer-use, memory, tool-use, workflow-agent
+- arXiv categories: cs.CL
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.13027

papers/items/2026-2607-13081-singguard-nsfa-extensible-guardrails-for-agentic-ai-via-generative-reasoning-and.md

@@ -0,0 +1,62 @@
+# Paper: SingGuard-NSFA: Extensible Guardrails for Agentic AI via Generative Reasoning and Real-Time Classification
+
+---
+type: paper
+title: "SingGuard-NSFA: Extensible Guardrails for Agentic AI via Generative Reasoning and Real-Time Classification"
+authors: SingGuard Team
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.13081
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - computer-use
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CR
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 16
+collection_queries: agent-safety, agentic-ai
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agent-safety, agentic-ai
+- inferred topics: agent-evaluation, agent-safety, computer-use, reasoning, tool-use
+- arXiv categories: cs.CR
+- collection score: 16
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.13081

papers/items/2026-2607-13085-baselines-before-architecture-evaluating-coding-agents-for-autonomous-penetratio.md

@@ -0,0 +1,61 @@
+# Paper: Baselines Before Architecture: Evaluating Coding Agents for Autonomous Penetration Testing
+
+---
+type: paper
+title: "Baselines Before Architecture: Evaluating Coding Agents for Autonomous Penetration Testing"
+authors: Ananda Dhakal, Krish Neupane, Aarjan Chaudhary
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.13085
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-13
+updated_at: 2026-07-13
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - coding-agent
+  - rag
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CR
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 16
+collection_queries: coding-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: coding-agent
+- inferred topics: agent-evaluation, agent-safety, coding-agent, rag
+- arXiv categories: cs.CR
+- collection score: 16
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.13085

papers/items/2026-2607-13196-from-human-centric-to-agentic-code-review-the-impact-of-different-generations-of.md

@@ -0,0 +1,61 @@
+# Paper: From Human-Centric to Agentic Code Review: The Impact of Different Generations of Generative AI Technology on Review Quality
+
+---
+type: paper
+title: "From Human-Centric to Agentic Code Review: The Impact of Different Generations of Generative AI Technology on Review Quality"
+authors: Suzhen Zhong, Shayan Noei, Bram Adams, Ying Zou
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.13196
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-14
+updated_at: 2026-07-14
+status: queued
+relevance: high
+topics:
+  - computer-use
+  - multi-agent
+  - planning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.SE
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: ai-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: ai-agent
+- inferred topics: computer-use, multi-agent, planning, tool-use
+- arXiv categories: cs.SE
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.13196

papers/items/2026-2607-13591-memory-as-a-controlled-process-learned-adaptive-memory-management-for-llm-agents.md

@@ -0,0 +1,61 @@
+# Paper: Memory as a Controlled Process: Learned Adaptive Memory Management for LLM Agents
+
+---
+type: paper
+title: "Memory as a Controlled Process: Learned Adaptive Memory Management for LLM Agents"
+authors: Eric Hanchen Jiang, Zhi Zhang, Yuchen Wu, Levina Li, Dong Liu, Xiao Liang, Rui Sun, Yubei Li, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.13591
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-15
+updated_at: 2026-07-15
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - memory
+  - planning
+  - rag
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CL
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 19
+collection_queries: planning-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: planning-agent
+- inferred topics: agent-evaluation, memory, planning, rag
+- arXiv categories: cs.CL
+- collection score: 19
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.13591

papers/items/2026-2607-13618-stocktake-measuring-the-gap-between-perception-and-action-in-llm-agents-with-a-f.md

@@ -0,0 +1,59 @@
+# Paper: STOCKTAKE: Measuring the Gap Between Perception and Action in LLM Agents with a Fair Oracle
+
+---
+type: paper
+title: "STOCKTAKE: Measuring the Gap Between Perception and Action in LLM Agents with a Fair Oracle"
+authors: Sagar Deb, Ashwanth Krishnan
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.13618
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-15
+updated_at: 2026-07-15
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: llm-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent
+- inferred topics: agent-evaluation, tool-use
+- arXiv categories: cs.AI
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.13618

papers/items/2026-2607-13705-agentcompass-a-unified-evaluation-infrastructure-for-agent-capabilities.md

@@ -0,0 +1,60 @@
+# Paper: AgentCompass: A Unified Evaluation Infrastructure for Agent Capabilities
+
+---
+type: paper
+title: "AgentCompass: A Unified Evaluation Infrastructure for Agent Capabilities"
+authors: Kai Chen, Zichen Ding, Jiaye Ge, Shufan Jiang, Mo Li, Qingqiu Li, Zehao Li, Zonglin Li, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.13705
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-20
+updated_at: 2026-07-20
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: autonomous-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: autonomous-agent-llm
+- inferred topics: agent-evaluation, rag, tool-use
+- arXiv categories: cs.AI
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.13705

papers/items/2026-2607-13854-spyce-skill-policy-co-evolution-for-multimodal-agents.md

@@ -0,0 +1,64 @@
+# Paper: SPyCE: Skill-Policy Co-evolution for Multimodal Agents
+
+---
+type: paper
+title: "SPyCE: Skill-Policy Co-evolution for Multimodal Agents"
+authors: Ru Zhang, Weijie Qiu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.13854
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-15
+updated_at: 2026-07-15
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+  - memory
+  - rag
+  - reasoning
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CL
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: tool-use
+- inferred topics: agent-evaluation, computer-use, memory, rag, reasoning, tool-use, workflow-agent
+- arXiv categories: cs.CL
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.13854

papers/items/2026-2607-13987-agent-skill-security-threat-models-attacks-defenses-and-evaluation.md

@@ -0,0 +1,62 @@
+# Paper: Agent Skill Security: Threat Models, Attacks, Defenses, and Evaluation
+
+---
+type: paper
+title: "Agent Skill Security: Threat Models, Attacks, Defenses, and Evaluation"
+authors: Sanket Badhe, Priyanka Tiwari
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.13987
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-15
+updated_at: 2026-07-15
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - coding-agent
+  - planning
+  - rag
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CR
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: llm-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent
+- inferred topics: agent-evaluation, agent-safety, coding-agent, planning, rag
+- arXiv categories: cs.CR
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.13987

papers/items/2026-2607-14145-toolanchor-anchoring-counterfactual-context-to-boost-agentic-tool-use-capability.md

@@ -0,0 +1,61 @@
+# Paper: ToolAnchor: Anchoring Counterfactual Context to Boost Agentic Tool-use Capability
+
+---
+type: paper
+title: "ToolAnchor: Anchoring Counterfactual Context to Boost Agentic Tool-use Capability"
+authors: Weiting Liu, Jieyi Bi, Wanqi Zhou, Jianfeng Feng, Yining Ma, Ai Han, Wenlian Lu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.14145
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-14
+updated_at: 2026-07-14
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - planning
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: tool-use
+- inferred topics: agent-evaluation, planning, reasoning, tool-use
+- arXiv categories: cs.AI
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.14145

papers/items/2026-2607-14165-towards-reliable-ai-assisted-analog-design-template-constrained-llm-agents-for-s.md

@@ -0,0 +1,61 @@
+# Paper: Towards Reliable AI-Assisted Analog Design: Template-Constrained LLM Agents for SAR ADC Generation
+
+---
+type: paper
+title: "Towards Reliable AI-Assisted Analog Design: Template-Constrained LLM Agents for SAR ADC Generation"
+authors: Dimple Vijay Kochar, Hae-Seung Lee, Anantha P. Chandrakasan
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.14165
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-15
+updated_at: 2026-07-15
+status: queued
+relevance: high
+topics:
+  - planning
+  - rag
+  - workflow-agent
+  - world-model
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.SE
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 16
+collection_queries: llm-agent, planning-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent, planning-agent
+- inferred topics: planning, rag, workflow-agent, world-model
+- arXiv categories: cs.SE
+- collection score: 16
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.14165

papers/items/2026-2607-14178-reasflow-assisting-reasoning-centric-scientific-discovery-in-applied-mathematics.md

@@ -0,0 +1,61 @@
+# Paper: ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System
+
+---
+type: paper
+title: "ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System"
+authors: Yutong He, Daibo Li, Guohong Li, Jiahe Geng, Zhengyang Huang, Can Ren, Zekun Zhang, Yifan Liu, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.14178
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-15
+updated_at: 2026-07-15
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - multi-agent
+  - rag
+  - reasoning
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 18
+collection_queries: ai-agent, autonomous-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: ai-agent, autonomous-agent-llm
+- inferred topics: agent-evaluation, multi-agent, rag, reasoning
+- arXiv categories: cs.AI
+- collection score: 18
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.14178

papers/items/2026-2607-14264-monteret-ai-agent-enhancing-multimodal-llms-with-multi-granularity-knowledge-ret.md

@@ -0,0 +1,61 @@
+# Paper: MonteRET: AI Agent Enhancing Multimodal LLMs with Multi-granularity Knowledge Retrieval for Chest CT Report Generation
+
+---
+type: paper
+title: "MonteRET: AI Agent Enhancing Multimodal LLMs with Multi-granularity Knowledge Retrieval for Chest CT Report Generation"
+authors: Yi Lin, Yihao Ding, Elana Benishay, Elefterios Trikantzopoulos, David Nauheim, Hanley Ong, Jiang Bian, Hua Xu, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.14264
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-15
+updated_at: 2026-07-15
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - computer-use
+  - rag
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CV
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: ai-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: ai-agent
+- inferred topics: agent-evaluation, agent-safety, computer-use, rag
+- arXiv categories: cs.CV
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.14264

papers/items/2026-2607-14277-multi-head-latent-control-a-unified-interface-for-llm-agent-decision-making.md

@@ -0,0 +1,61 @@
+# Paper: Multi-Head Latent Control: A Unified Interface for LLM Agent Decision Making
+
+---
+type: paper
+title: "Multi-Head Latent Control: A Unified Interface for LLM Agent Decision Making"
+authors: Amirhosein Ghasemabadi, Ruichen Chen, Bahador Rashidi, Di Niu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.14277
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-15
+updated_at: 2026-07-15
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - rag
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CL
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 18
+collection_queries: llm-agent, tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent, tool-use
+- inferred topics: agent-evaluation, rag, reasoning, tool-use
+- arXiv categories: cs.CL
+- collection score: 18
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.14277

papers/items/2026-2607-14386-cipher-a-decoupled-exploration-selection-framework-for-test-time-scaling-of-data.md

@@ -0,0 +1,61 @@
+# Paper: CIPHER: A Decoupled Exploration-Selection Framework for Test-Time Scaling of Data Science Agents
+
+---
+type: paper
+title: "CIPHER: A Decoupled Exploration-Selection Framework for Test-Time Scaling of Data Science Agents"
+authors: Maxime Heuillet, Sharadind Peddiraju
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.14386
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-15
+updated_at: 2026-07-15
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - rag
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: ai-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: ai-agent
+- inferred topics: agent-evaluation, rag, tool-use, workflow-agent
+- arXiv categories: cs.AI
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.14386

papers/items/2026-2607-14456-beyond-generalist-llms-specialist-agentic-systems-for-structured-code-workflow-e.md

@@ -0,0 +1,59 @@
+# Paper: Beyond Generalist LLMs: Specialist Agentic Systems for Structured Code Workflow Execution
+
+---
+type: paper
+title: "Beyond Generalist LLMs: Specialist Agentic Systems for Structured Code Workflow Execution"
+authors: Harris Borman, Herman Wandabwa, Fusun Yu, Sandeepa Kannangara, Justin Liu, Anna Leontjeva, Ritchie Ng
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.14456
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-15
+updated_at: 2026-07-15
+status: queued
+relevance: high
+topics:
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.SE
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: agentic-ai, tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agentic-ai, tool-use
+- inferred topics: tool-use, workflow-agent
+- arXiv categories: cs.SE
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.14456

papers/items/2026-2607-14548-hymobileagent-data-environment-co-scaling-for-efficient-gui-agents.md

@@ -0,0 +1,62 @@
+# Paper: HyMobileAgent: Data-Environment Co-Scaling for Efficient GUI Agents
+
+---
+type: paper
+title: "HyMobileAgent: Data-Environment Co-Scaling for Efficient GUI Agents"
+authors: Hy Vision Team, Huawen Shen, Zhengyang Tang, Shangpin Peng, Liang Wu, Anran Zhang, Weinong Wang, Yiduo Guo, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.14548
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-16
+updated_at: 2026-07-16
+status: queued
+relevance: high
+topics:
+  - computer-use
+  - embodied-agent
+  - planning
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CV
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: web-gui-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: web-gui-agent
+- inferred topics: computer-use, embodied-agent, planning, reasoning, tool-use
+- arXiv categories: cs.CV
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.14548

papers/items/2026-2607-14573-alipay-pibench-a-realistic-payment-integration-benchmark-for-coding-agents.md

@@ -0,0 +1,63 @@
+# Paper: Alipay-PIBench: A Realistic Payment Integration Benchmark for Coding Agents
+
+---
+type: paper
+title: "Alipay-PIBench: A Realistic Payment Integration Benchmark for Coding Agents"
+authors: Shiyu Ying, Xuejie Cao, Yingfan Ma, Yuanhao Dong, Wenyu Chen, Bowen Song, Lin Zhu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.14573
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-21
+updated_at: 2026-07-21
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - coding-agent
+  - computer-use
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 19
+collection_queries: coding-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: coding-agent
+- inferred topics: agent-evaluation, agent-safety, coding-agent, computer-use, rag, tool-use
+- arXiv categories: cs.AI
+- collection score: 19
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.14573

papers/items/2026-2607-14642-mcpevol-bench-benchmarking-llm-agent-performance-across-dynamic-evolutions-of-mc.md

@@ -0,0 +1,63 @@
+# Paper: MCPEvol-Bench: Benchmarking LLM Agent Performance Across Dynamic Evolutions of MCP Servers
+
+---
+type: paper
+title: "MCPEvol-Bench: Benchmarking LLM Agent Performance Across Dynamic Evolutions of MCP Servers"
+authors: Huanxi Liu, Kun Hu, Jiaqi Liao, Qiang Wang, Pengfei Qian, YuanZhao Zhai, Dawei Feng, Bo Ding, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.14642
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-16
+updated_at: 2026-07-16
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - planning
+  - rag
+  - reasoning
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 21
+collection_queries: llm-agent, planning-agent, tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent, planning-agent, tool-use
+- inferred topics: agent-evaluation, planning, rag, reasoning, tool-use, workflow-agent
+- arXiv categories: cs.AI
+- collection score: 21
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.14642

papers/items/2026-2607-14651-mempoison-uncovering-persistent-memory-threats-and-structural-blind-spots-in-llm.md

@@ -0,0 +1,62 @@
+# Paper: MemPoison: Uncovering Persistent Memory Threats and Structural Blind Spots in LLM Agents
+
+---
+type: paper
+title: "MemPoison: Uncovering Persistent Memory Threats and Structural Blind Spots in LLM Agents"
+authors: Jifeng Gao, Kang Xia, Yi Zhang, Xiaobin Hong, Mingkai Lin, Xingshen Wei, Wenzhong Li, Sanglu Lu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.14651
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-16
+updated_at: 2026-07-16
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - memory
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CR
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 20
+collection_queries: llm-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent
+- inferred topics: agent-evaluation, agent-safety, memory, rag, tool-use
+- arXiv categories: cs.CR
+- collection score: 20
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.14651

papers/items/2026-2607-14777-seed-self-evolving-on-policy-distillation-for-agentic-reinforcement-learning.md

@@ -0,0 +1,61 @@
+# Paper: SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning
+
+---
+type: paper
+title: "SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning"
+authors: Jinyang Wu, Shuo Yang, Zhengxi Lu, Fan Zhang, Yuhao Shen, Lang Feng, Haoran Luo, Zheng Lian, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.14777
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-16
+updated_at: 2026-07-16
+status: queued
+relevance: high
+topics:
+  - computer-use
+  - planning
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CL
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: tool-use
+- inferred topics: computer-use, planning, tool-use, workflow-agent
+- arXiv categories: cs.CL
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.14777

papers/items/2026-2607-14989-omniabench-benchmarking-general-ai-agents-across-diverse-scenarios.md

@@ -0,0 +1,61 @@
+# Paper: OmniaBench: Benchmarking General AI Agents Across Diverse Scenarios
+
+---
+type: paper
+title: "OmniaBench: Benchmarking General AI Agents Across Diverse Scenarios"
+authors: Chengyu Shen, Yujie Fu, Gangtao Xin, Yanheng Hou, Wenlong Fei, Guojie Zhu, Jiawei Li, Hongcheng Gao, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.14989
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-16
+updated_at: 2026-07-16
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - planning
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CL
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 19
+collection_queries: agent-evaluation, ai-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agent-evaluation, ai-agent
+- inferred topics: agent-evaluation, planning, rag, tool-use
+- arXiv categories: cs.CL
+- collection score: 19
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.14989

papers/items/2026-2607-15079-brainpilot-automating-brain-discovery-with-agentic-research.md

@@ -0,0 +1,63 @@
+# Paper: BrainPilot: Automating Brain Discovery with Agentic Research
+
+---
+type: paper
+title: "BrainPilot: Automating Brain Discovery with Agentic Research"
+authors: Haoxuan Li, Tianci Gao, Jianhe Li, Yang Fan, Runze Shi, Weiran Wang, Tianxiang Zhao, Zezhao Wu, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.15079
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-17
+updated_at: 2026-07-17
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - multi-agent
+  - rag
+  - reasoning
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 20
+collection_queries: ai-agent, tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: ai-agent, tool-use
+- inferred topics: agent-evaluation, multi-agent, rag, reasoning, tool-use, workflow-agent
+- arXiv categories: cs.AI
+- collection score: 20
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.15079

papers/items/2026-2607-15193-plover-steering-gui-agents-through-plan-centric-interaction.md

@@ -0,0 +1,62 @@
+# Paper: Plover: Steering GUI Agents through Plan-Centric Interaction
+
+---
+type: paper
+title: "Plover: Steering GUI Agents through Plan-Centric Interaction"
+authors: Madhumitha Venkatesan, Shicheng Wen, Jiajing Guo, Jorge Piazentin Ono, Liu Ren, Dongyu Liu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.15193
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-16
+updated_at: 2026-07-16
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+  - planning
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: web-gui-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: web-gui-agent
+- inferred topics: agent-evaluation, computer-use, planning, tool-use, workflow-agent
+- arXiv categories: cs.AI
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.15193

papers/items/2026-2607-15246-armor-agentic-orchestration-of-a-multi-domain-primitive-set-for-transferable-att.md

@@ -0,0 +1,60 @@
+# Paper: ARMOR++: Agentic Orchestration of a Multi-Domain Primitive Set for Transferable Attacks on Deepfake Detectors
+
+---
+type: paper
+title: "ARMOR++: Agentic Orchestration of a Multi-Domain Primitive Set for Transferable Attacks on Deepfake Detectors"
+authors: Christos Korgialas, Gabriel Lee Jun Rong, Dion Jia Xu Ho, Pai Chet Ng, Xiaoxiao Miao, Konstantinos N. Plataniotis
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.15246
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-16
+updated_at: 2026-07-16
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - multi-agent
+  - rag
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CV
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 17
+collection_queries: agent-evaluation, multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agent-evaluation, multi-agent-llm
+- inferred topics: agent-evaluation, multi-agent, rag
+- arXiv categories: cs.CV
+- collection score: 17
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.15246

papers/items/2026-2607-15263-beyond-success-rate-cost-aware-evaluation-of-offensive-and-defensive-security-ag.md

@@ -0,0 +1,62 @@
+# Paper: Beyond Success Rate: Cost-Aware Evaluation of Offensive and Defensive Security Agents
+
+---
+type: paper
+title: "Beyond Success Rate: Cost-Aware Evaluation of Offensive and Defensive Security Agents"
+authors: Paul Kassianik, Blaine Nelson, Yaron Singer
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.15263
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-17
+updated_at: 2026-07-17
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - embodied-agent
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CR
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 16
+collection_queries: agent-evaluation, tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agent-evaluation, tool-use
+- inferred topics: agent-evaluation, agent-safety, embodied-agent, reasoning, tool-use
+- arXiv categories: cs.CR
+- collection score: 16
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.15263

papers/items/2026-2607-15367-anovax-a-local-multi-agent-voice-assistant-with-llm-planning-typed-executors-and.md

@@ -0,0 +1,63 @@
+# Paper: AnovaX: A Local, Multi-Agent Voice Assistant with LLM Planning, Typed Executors, and Adaptive Recovery
+
+---
+type: paper
+title: "AnovaX: A Local, Multi-Agent Voice Assistant with LLM Planning, Typed Executors, and Adaptive Recovery"
+authors: Raunak B Sinha
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.15367
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-16
+updated_at: 2026-07-16
+status: queued
+relevance: high
+topics:
+  - agent-safety
+  - computer-use
+  - multi-agent
+  - planning
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 16
+collection_queries: multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm
+- inferred topics: agent-safety, computer-use, multi-agent, planning, rag, tool-use
+- arXiv categories: cs.AI
+- collection score: 16
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.15367

papers/items/2026-2607-15434-coercion-and-deception-in-ai-to-ai-management-an-agentic-benchmark-of-unprompted.md

@@ -0,0 +1,60 @@
+# Paper: Coercion and Deception in AI-to-AI Management: An Agentic Benchmark of Unprompted Escalation
+
+---
+type: paper
+title: "Coercion and Deception in AI-to-AI Management: An Agentic Benchmark of Unprompted Escalation"
+authors: Jasmine Brazilek, Maheep Chaudhary, Zoe Lu, Miles Tidmarsh
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.15434
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-22
+updated_at: 2026-07-22
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - multi-agent
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.MA
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 21
+collection_queries: agent-evaluation, ai-agent, multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agent-evaluation, ai-agent, multi-agent-llm
+- inferred topics: agent-evaluation, multi-agent, tool-use
+- arXiv categories: cs.MA
+- collection score: 21
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.15434

papers/items/2026-2607-15518-a-tool-invariant-framework-for-teaching-and-assessing-computational-methods-in-t.md

@@ -0,0 +1,61 @@
+# Paper: A Tool-Invariant Framework for Teaching and Assessing Computational Methods in the Age of Agentic AI
+
+---
+type: paper
+title: A Tool-Invariant Framework for Teaching and Assessing Computational Methods in the Age of Agentic AI
+authors: Larry Engelhardt
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.15518
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-16
+updated_at: 2026-07-16
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - tool-use
+  - world-model
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - physics.ed-ph
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: agentic-ai, language-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agentic-ai, language-agent
+- inferred topics: agent-evaluation, coding-agent, tool-use, world-model
+- arXiv categories: physics.ed-ph
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.15518

papers/items/2026-2607-15535-symbolic-predicate-guided-language-agents-for-inverse-design-of-perovskite-oxide.md

@@ -0,0 +1,62 @@
+# Paper: Symbolic Predicate-Guided Language Agents for Inverse Design of Perovskite Oxides
+
+---
+type: paper
+title: Symbolic Predicate-Guided Language Agents for Inverse Design of Perovskite Oxides
+authors: Dong Hyeon Mok, Seoin Back, Victor Fung, Guoxiang Hu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.15535
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-16
+updated_at: 2026-07-16
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+  - multi-agent
+  - rag
+  - reasoning
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cond-mat.mtrl-sci
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 19
+collection_queries: language-agent, llm-agent, multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: language-agent, llm-agent, multi-agent-llm
+- inferred topics: agent-evaluation, computer-use, multi-agent, rag, reasoning
+- arXiv categories: cond-mat.mtrl-sci
+- collection score: 19
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.15535

papers/items/2026-2607-15557-skillcorpus-consolidating-and-evaluating-the-open-skill-ecosystem-for-real-world.md

@@ -0,0 +1,60 @@
+# Paper: SkillCorpus: Consolidating and Evaluating the Open Skill Ecosystem for Real-World LLM Agents
+
+---
+type: paper
+title: "SkillCorpus: Consolidating and Evaluating the Open Skill Ecosystem for Real-World LLM Agents"
+authors: Yanze Wang, Pengfei Yao, Tianyi Sun, Chuanrui Hu, Yan Xiao, Yunyun Han, Yifan Chen, Jun Sun, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.15557
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-23
+updated_at: 2026-07-23
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - rag
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CL
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: llm-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent
+- inferred topics: agent-evaluation, agent-safety, rag
+- arXiv categories: cs.CL
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.15557

papers/items/2026-2607-15593-scalable-llm-agent-tool-access-in-the-cloud.md

@@ -0,0 +1,62 @@
+# Paper: Scalable LLM Agent Tool Access in the Cloud
+
+---
+type: paper
+title: Scalable LLM Agent Tool Access in the Cloud
+authors: Mingxin Li, Enge Song, Yueshang Zuo, Xiaodong Liu, Rong Wen, Qiang Fu, Gianni Antichi, Jian He, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.15593
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-16
+updated_at: 2026-07-16
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - memory
+  - planning
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.DC
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 15
+collection_queries: llm-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent
+- inferred topics: agent-evaluation, memory, planning, rag, tool-use
+- arXiv categories: cs.DC
+- collection score: 15
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.15593

papers/items/2026-2607-15660-toolverse-unlocking-massive-environments-and-long-horizon-tasks-for-agentic-rein.md

@@ -0,0 +1,62 @@
+# Paper: ToolVerse: Unlocking Massive Environments and Long-Horizon Tasks for Agentic Reinforcement Learning
+
+---
+type: paper
+title: "ToolVerse: Unlocking Massive Environments and Long-Horizon Tasks for Agentic Reinforcement Learning"
+authors: Shuaiyu Zhou, Fengpeng Yue, Zengjie Hu, Yuanzhe Shen, Chenyang Zhang, feng hong, Cao Liu, Ke Zeng
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.15660
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-17
+updated_at: 2026-07-17
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - planning
+  - reasoning
+  - tool-use
+  - world-model
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 20
+collection_queries: agent-evaluation, llm-agent, tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agent-evaluation, llm-agent, tool-use
+- inferred topics: agent-evaluation, planning, reasoning, tool-use, world-model
+- arXiv categories: cs.AI
+- collection score: 20
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.15660

papers/items/2026-2607-15715-behavioral-controllability-of-agentic-models-for-information-extraction-from-fix.md

@@ -0,0 +1,63 @@
+# Paper: Behavioral Controllability of Agentic Models for Information Extraction: From Fixed Workflows to Reflective Agents
+
+---
+type: paper
+title: "Behavioral Controllability of Agentic Models for Information Extraction: From Fixed Workflows to Reflective Agents"
+authors: Lujia Zhang, Xingzhou Chen, Hongwei Feng
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.15715
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-17
+updated_at: 2026-07-17
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - memory
+  - rag
+  - reasoning
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 18
+collection_queries: llm-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent
+- inferred topics: agent-evaluation, memory, rag, reasoning, tool-use, workflow-agent
+- arXiv categories: cs.AI
+- collection score: 18
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.15715

papers/items/2026-2607-15781-agentfair-a-multi-agent-collaborative-framework-for-fairness-evaluation-of-geosp.md

@@ -0,0 +1,64 @@
+# Paper: AgentFAIR: A Multi-Agent Collaborative Framework for FAIRness Evaluation of Geospatial Datasets
+
+---
+type: paper
+title: "AgentFAIR: A Multi-Agent Collaborative Framework for FAIRness Evaluation of Geospatial Datasets"
+authors: Ming Chen, Pranav Pai
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.15781
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-24
+updated_at: 2026-07-24
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - coding-agent
+  - multi-agent
+  - planning
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 21
+collection_queries: multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm
+- inferred topics: agent-evaluation, agent-safety, coding-agent, multi-agent, planning, rag, tool-use
+- arXiv categories: cs.AI
+- collection score: 21
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.15781

papers/items/2026-2607-16057-frontier-ai-performance-across-the-business-disciplines-a-case-grounded-benchmar.md

@@ -0,0 +1,61 @@
+# Paper: Frontier AI performance across the business disciplines: a case-grounded benchmark of knowledge work and analytical reasoning
+
+---
+type: paper
+title: "Frontier AI performance across the business disciplines: a case-grounded benchmark of knowledge work and analytical reasoning"
+authors: Ajay Patel, Kartik Hosanagar, Ramayya Krishnan, Chris Callison-Burch, Karim Lakhani
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.16057
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-20
+updated_at: 2026-07-20
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CL
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: tool-use
+- inferred topics: agent-evaluation, coding-agent, reasoning, tool-use
+- arXiv categories: cs.CL
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.16057

papers/items/2026-2607-16133-when-do-multi-agent-systems-help-an-information-bottleneck-perspective.md

@@ -0,0 +1,60 @@
+# Paper: When Do Multi-Agent Systems Help? An Information Bottleneck Perspective
+
+---
+type: paper
+title: When Do Multi-Agent Systems Help? An Information Bottleneck Perspective
+authors: Wendi Yu, Lianhao Zhou, Xiangjue Dong, Sai Sudarshan Barath, Declan Staunton, Byung-Jun Yoon, Xiaoning Qian, James Caverlee, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.16133
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-17
+updated_at: 2026-07-17
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - multi-agent
+  - reasoning
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.LG
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm
+- inferred topics: agent-evaluation, multi-agent, reasoning
+- arXiv categories: cs.LG
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.16133

papers/items/2026-2607-16610-just-a-rather-very-intelligent-spoken-agent.md

@@ -0,0 +1,63 @@
+# Paper: Just A Rather Very Intelligent Spoken Agent
+
+---
+type: paper
+title: Just A Rather Very Intelligent Spoken Agent
+authors: Chen Chen, Zhehuai Chen
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.16610
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-17
+updated_at: 2026-07-17
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+  - multi-agent
+  - planning
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 16
+collection_queries: agentic-ai, ai-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agentic-ai, ai-agent
+- inferred topics: agent-evaluation, computer-use, multi-agent, planning, tool-use, workflow-agent
+- arXiv categories: cs.AI
+- collection score: 16
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.16610

papers/items/2026-2607-16708-model-driven-discipline-for-multi-agent-llms-requirement-to-verification-generat.md

@@ -0,0 +1,61 @@
+# Paper: Model-Driven Discipline for Multi-Agent LLMs: Requirement-to-Verification Generation of Traceable System Models
+
+---
+type: paper
+title: "Model-Driven Discipline for Multi-Agent LLMs: Requirement-to-Verification Generation of Traceable System Models"
+authors: Ran Wei, Le Zhu, Haochi Wang, Ruizhe Yang, Jiapeng Guan, Siyuan Ji, Yuchen Hu, Zhe Jiang, et al.
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.16708
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-18
+updated_at: 2026-07-18
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - multi-agent
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.SE
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: multi-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: multi-agent-llm
+- inferred topics: agent-evaluation, agent-safety, multi-agent, tool-use
+- arXiv categories: cs.SE
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.16708

papers/items/2026-2607-16851-agentbrew-lifelong-knowledge-brewing-from-strong-teachers-to-weak-llm-agents.md

@@ -0,0 +1,62 @@
+# Paper: AgentBrew: Lifelong Knowledge Brewing from Strong Teachers to Weak LLM Agents
+
+---
+type: paper
+title: "AgentBrew: Lifelong Knowledge Brewing from Strong Teachers to Weak LLM Agents"
+authors: Yangqin Jiang, Chao Huang
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.16851
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-18
+updated_at: 2026-07-18
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - computer-use
+  - memory
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 18
+collection_queries: llm-agent, tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent, tool-use
+- inferred topics: agent-evaluation, coding-agent, computer-use, memory, tool-use
+- arXiv categories: cs.AI
+- collection score: 18
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.16851

papers/items/2026-2607-16900-environment-free-synthetic-data-generation-for-api-calling-agents.md

@@ -0,0 +1,63 @@
+# Paper: Environment-free Synthetic Data Generation for API-Calling Agents
+
+---
+type: paper
+title: Environment-free Synthetic Data Generation for API-Calling Agents
+authors: Seanie Lee, Sanjoy Chowdhury, Chao Jiang, Cheng-Yu Hsieh, Ting-Yao Hu, Alexander T Toshev, Oncel Tuzel, Raviteja Vemulapalli
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.16900
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-21
+updated_at: 2026-07-21
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - memory
+  - rag
+  - tool-use
+  - workflow-agent
+  - world-model
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: llm-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent
+- inferred topics: agent-evaluation, memory, rag, tool-use, workflow-agent, world-model
+- arXiv categories: cs.AI
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.16900

papers/items/2026-2607-17050-evogui-an-evolution-aware-benchmark-for-gui-state-transition-understanding.md

@@ -0,0 +1,62 @@
+# Paper: EvoGUI: An Evolution-Aware Benchmark for GUI State-Transition Understanding
+
+---
+type: paper
+title: "EvoGUI: An Evolution-Aware Benchmark for GUI State-Transition Understanding"
+authors: Yaohan Yang, Minglei Shi, Borui Zhang, Jie Zhou, Jiwen Lu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.17050
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-18
+updated_at: 2026-07-18
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+  - planning
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.CV
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 16
+collection_queries: agent-evaluation, web-gui-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agent-evaluation, web-gui-agent
+- inferred topics: agent-evaluation, computer-use, planning, rag, tool-use
+- arXiv categories: cs.CV
+- collection score: 16
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.17050

papers/items/2026-2607-17149-a-diagnostic-framework-for-ai-agent-behavior.md

@@ -0,0 +1,60 @@
+# Paper: A Diagnostic Framework for AI Agent Behavior
+
+---
+type: paper
+title: A Diagnostic Framework for AI Agent Behavior
+authors: Xichen Zhang, Yingjie Zhang, Tianshu Sun
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.17149
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-19
+updated_at: 2026-07-19
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - memory
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: ai-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: ai-agent
+- inferred topics: agent-evaluation, memory, tool-use
+- arXiv categories: cs.AI
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.17149

papers/items/2026-2607-17288-saga-synthetic-agentic-graph-architecture-for-temporal-benchmark-generation.md

@@ -0,0 +1,60 @@
+# Paper: SAGA: Synthetic Agentic Graph Architecture for Temporal Benchmark Generation
+
+---
+type: paper
+title: "SAGA: Synthetic Agentic Graph Architecture for Temporal Benchmark Generation"
+authors: Jiacheng Ding, Xiaofei Zhang
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.17288
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-19
+updated_at: 2026-07-19
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - rag
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.DB
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 18
+collection_queries: llm-agent, rag-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent, rag-agent
+- inferred topics: agent-evaluation, agent-safety, rag
+- arXiv categories: cs.DB
+- collection score: 18
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.17288

papers/items/2026-2607-17331-agentic-erp-multi-agent-large-language-model-architecture-for-autonomous-enterpr.md

@@ -0,0 +1,64 @@
+# Paper: Agentic ERP: Multi-Agent Large Language Model Architecture for Autonomous Enterprise Resource Planning
+
+---
+type: paper
+title: "Agentic ERP: Multi-Agent Large Language Model Architecture for Autonomous Enterprise Resource Planning"
+authors: Zhihao Liu, Tianyu Wang, Xi Vincent Wang, Lihui Wang
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.17331
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-19
+updated_at: 2026-07-19
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - multi-agent
+  - planning
+  - tool-use
+  - workflow-agent
+  - world-model
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 24
+collection_queries: llm-agent, multi-agent-llm, planning-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent, multi-agent-llm, planning-agent
+- inferred topics: agent-evaluation, agent-safety, multi-agent, planning, tool-use, workflow-agent, world-model
+- arXiv categories: cs.AI
+- collection score: 24
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.17331

papers/items/2026-2607-17437-empirical-grounding-improves-the-realism-of-llm-agents-simulating-human-behavior.md

@@ -0,0 +1,63 @@
+# Paper: Empirical Grounding Improves the Realism of LLM Agents Simulating Human Behavior During Disruptions
+
+---
+type: paper
+title: Empirical Grounding Improves the Realism of LLM Agents Simulating Human Behavior During Disruptions
+authors: Chen Xia, Zexi Kuang, Yuqing Hu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.17437
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-19
+updated_at: 2026-07-19
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - memory
+  - planning
+  - rag
+  - reasoning
+  - world-model
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 19
+collection_queries: llm-agent, planning-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: llm-agent, planning-agent
+- inferred topics: agent-evaluation, memory, planning, rag, reasoning, world-model
+- arXiv categories: cs.AI
+- collection score: 19
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.17437

papers/items/2026-2607-17527-sidekick-designing-communication-for-effective-multitasking-with-computer-use-ag.md

@@ -0,0 +1,62 @@
+# Paper: Sidekick: Designing Communication for Effective Multitasking with Computer Use Agents
+
+---
+type: paper
+title: "Sidekick: Designing Communication for Effective Multitasking with Computer Use Agents"
+authors: Ruei-Che Chang, Wenqian Xu, Dingzeyu Li, Bryan Wang, Anhong Guo
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.17527
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-20
+updated_at: 2026-07-20
+status: queued
+relevance: high
+topics:
+  - computer-use
+  - multi-agent
+  - planning
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.HC
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 13
+collection_queries: web-gui-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: web-gui-agent
+- inferred topics: computer-use, multi-agent, planning, reasoning, tool-use
+- arXiv categories: cs.HC
+- collection score: 13
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.17527

papers/items/2026-2607-17528-can-ai-agents-really-complete-rtl-to-gds-lessons-from-benchmarking-tool-interact.md

@@ -0,0 +1,62 @@
+# Paper: Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows
+
+---
+type: paper
+title: Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows
+authors: Jinyuan Deng, Zhengrui Chen, Xufeng Wei, Tianyu Xing, Chenyi Wen, Qi Sun, Cheng Zhuo
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.17528
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-22
+updated_at: 2026-07-22
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - coding-agent
+  - planning
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 23
+collection_queries: ai-agent, coding-agent, llm-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: ai-agent, coding-agent, llm-agent
+- inferred topics: agent-evaluation, coding-agent, planning, tool-use, workflow-agent
+- arXiv categories: cs.AI
+- collection score: 23
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.17528

papers/items/2026-2607-17545-retain-or-consolidate-budget-dependent-operator-selection-for-language-agent-mem.md

@@ -0,0 +1,62 @@
+# Paper: Retain or Consolidate? Budget-Dependent Operator Selection for Language Agent Memory
+
+---
+type: paper
+title: Retain or Consolidate? Budget-Dependent Operator Selection for Language Agent Memory
+authors: Qingcan Kang, Mingyang Liu, Shixiong Kai, Kaichao Liang, Zhentao Tang, Yuqi Cui, Tao Zhong, Mingxuan Yuan
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.17545
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-20
+updated_at: 2026-07-20
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - agent-safety
+  - memory
+  - rag
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 20
+collection_queries: agent-memory, language-agent
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agent-memory, language-agent
+- inferred topics: agent-evaluation, agent-safety, memory, rag, tool-use
+- arXiv categories: cs.AI
+- collection score: 20
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.17545

papers/items/2026-2607-17621-mechanistic-attention-guidance-for-agent-memory-refinement.md

@@ -0,0 +1,62 @@
+# Paper: Mechanistic Attention Guidance for Agent Memory Refinement
+
+---
+type: paper
+title: Mechanistic Attention Guidance for Agent Memory Refinement
+authors: Yechao Hong, Haiquan Qiu, Yaqing Wang, Quanming Yao
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.17621
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-20
+updated_at: 2026-07-20
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - computer-use
+  - memory
+  - rag
+  - reasoning
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: agent-memory
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: agent-memory
+- inferred topics: agent-evaluation, computer-use, memory, rag, reasoning
+- arXiv categories: cs.AI
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.17621

papers/items/2026-2607-17879-exploratory-and-assimilating-reflection-reflective-recall-cycle-for-long-term-me.md

@@ -0,0 +1,62 @@
+# Paper: Exploratory and Assimilating Reflection: Reflective Recall Cycle for Long-term Memory
+
+---
+type: paper
+title: "Exploratory and Assimilating Reflection: Reflective Recall Cycle for Long-term Memory"
+authors: Ganesh Senrayan, Moyuru Yamada, Ishan Jindal, Kiran Purohit
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2607.17879
+code_url:
+source: arxiv
+collected_at: 2026-07-27
+published_at: 2026-07-20
+updated_at: 2026-07-20
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - memory
+  - rag
+  - reasoning
+  - tool-use
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: autonomous-agent-llm
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: autonomous-agent-llm
+- inferred topics: agent-evaluation, memory, rag, reasoning, tool-use
+- arXiv categories: cs.AI
+- collection score: 14
+
+## Review Checklist
+
+- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
+- Does it include a benchmark, dataset, code, or reproducible experimental setup?
+- Should it be promoted from `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2607.17879