[
  {
    "id": "2607.17331",
    "arxiv_id": "2607.17331",
    "source": "arxiv",
    "source_id": "arxiv:2607.17331",
    "title": "Agentic ERP: Multi-Agent Large Language Model Architecture for Autonomous Enterprise Resource Planning",
    "url": "https://arxiv.org/abs/2607.17331",
    "pdf_url": "https://arxiv.org/pdf/2607.17331",
    "published": "2026-07-19",
    "updated": "2026-07-19",
    "authors": [
      "Zhihao Liu",
      "Tianyu Wang",
      "Xi Vincent Wang",
      "Lihui Wang"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "multi-agent",
      "planning",
      "tool-use",
      "workflow-agent",
      "world-model"
    ],
    "score": 24,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent",
      "multi-agent-llm",
      "planning-agent"
    ]
  },
  {
    "id": "2607.17528",
    "arxiv_id": "2607.17528",
    "source": "arxiv",
    "source_id": "arxiv:2607.17528",
    "title": "Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows",
    "url": "https://arxiv.org/abs/2607.17528",
    "pdf_url": "https://arxiv.org/pdf/2607.17528",
    "published": "2026-07-22",
    "updated": "2026-07-22",
    "authors": [
      "Jinyuan Deng",
      "Zhengrui Chen",
      "Xufeng Wei",
      "Tianyu Xing",
      "Chenyi Wen",
      "Qi Sun",
      "Cheng Zhuo"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "planning",
      "tool-use",
      "workflow-agent"
    ],
    "score": 23,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent",
      "coding-agent",
      "llm-agent"
    ]
  },
  {
    "id": "2607.18366",
    "arxiv_id": "2607.18366",
    "source": "arxiv",
    "source_id": "arxiv:2607.18366",
    "title": "Operational Hallucination and Safety Drift in AI Agents",
    "url": "https://arxiv.org/abs/2607.18366",
    "pdf_url": "https://arxiv.org/pdf/2607.18366",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Shasha Yu",
      "Fiona Carroll",
      "Barry L. Bentley"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "computer-use",
      "planning",
      "reasoning",
      "tool-use",
      "world-model"
    ],
    "score": 22,
    "relevance": "high",
    "primary_query": "agentic-ai",
    "matched_queries": [
      "agentic-ai",
      "ai-agent",
      "autonomous-agent-llm",
      "tool-use"
    ]
  },
  {
    "id": "2607.10994",
    "arxiv_id": "2607.10994",
    "source": "arxiv",
    "source_id": "arxiv:2607.10994",
    "title": "A Multi-Agent Framework for Zero-Dimensional Reduced-Order Model Planning",
    "url": "https://arxiv.org/abs/2607.10994",
    "pdf_url": "https://arxiv.org/pdf/2607.10994",
    "published": "2026-07-12",
    "updated": "2026-07-12",
    "authors": [
      "Bingteng Sun",
      "Hao Yin",
      "Yiling Chen",
      "Renjie Xiao",
      "Lei Xie",
      "Shanyou Wang",
      "Ruonan Wang",
      "Shubao Chen",
      "Qingzong Xu",
      "Lin Lu",
      "Qiang Du",
      "Junqiang Zhu"
    ],
    "categories": [
      "cs.LG"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "embodied-agent",
      "multi-agent",
      "planning",
      "rag",
      "reasoning",
      "tool-use",
      "workflow-agent"
    ],
    "score": 22,
    "relevance": "high",
    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm",
      "planning-agent",
      "rag-agent"
    ]
  },
  {
    "id": "2607.15781",
    "arxiv_id": "2607.15781",
    "source": "arxiv",
    "source_id": "arxiv:2607.15781",
    "title": "AgentFAIR: A Multi-Agent Collaborative Framework for FAIRness Evaluation of Geospatial Datasets",
    "url": "https://arxiv.org/abs/2607.15781",
    "pdf_url": "https://arxiv.org/pdf/2607.15781",
    "published": "2026-07-24",
    "updated": "2026-07-24",
    "authors": [
      "Ming Chen",
      "Pranav Pai"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "coding-agent",
      "multi-agent",
      "planning",
      "rag",
      "tool-use"
    ],
    "score": 21,
    "relevance": "high",
    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.15434",
    "arxiv_id": "2607.15434",
    "source": "arxiv",
    "source_id": "arxiv:2607.15434",
    "title": "Coercion and Deception in AI-to-AI Management: An Agentic Benchmark of Unprompted Escalation",
    "url": "https://arxiv.org/abs/2607.15434",
    "pdf_url": "https://arxiv.org/pdf/2607.15434",
    "published": "2026-07-22",
    "updated": "2026-07-22",
    "authors": [
      "Jasmine Brazilek",
      "Maheep Chaudhary",
      "Zoe Lu",
      "Miles Tidmarsh"
    ],
    "categories": [
      "cs.MA"
    ],
    "topics": [
      "agent-evaluation",
      "multi-agent",
      "tool-use"
    ],
    "score": 21,
    "relevance": "high",
    "primary_query": "agent-evaluation",
    "matched_queries": [
      "agent-evaluation",
      "ai-agent",
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.14642",
    "arxiv_id": "2607.14642",
    "source": "arxiv",
    "source_id": "arxiv:2607.14642",
    "title": "MCPEvol-Bench: Benchmarking LLM Agent Performance Across Dynamic Evolutions of MCP Servers",
    "url": "https://arxiv.org/abs/2607.14642",
    "pdf_url": "https://arxiv.org/pdf/2607.14642",
    "published": "2026-07-16",
    "updated": "2026-07-16",
    "authors": [
      "Huanxi Liu",
      "Kun Hu",
      "Jiaqi Liao",
      "Qiang Wang",
      "Pengfei Qian",
      "YuanZhao Zhai",
      "Dawei Feng",
      "Bo Ding",
      "Huaimin Wang"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "planning",
      "rag",
      "reasoning",
      "tool-use",
      "workflow-agent"
    ],
    "score": 21,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent",
      "planning-agent",
      "tool-use"
    ]
  },
  {
    "id": "2607.21106",
    "arxiv_id": "2607.21106",
    "source": "arxiv",
    "source_id": "arxiv:2607.21106",
    "title": "AttriMem: Attribution-Guided Process Feedback for Agent Memory Learning",
    "url": "https://arxiv.org/abs/2607.21106",
    "pdf_url": "https://arxiv.org/pdf/2607.21106",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Qinfeng Li",
      "Yuntai Bao",
      "Xinyan Yu",
      "Hongze Chen",
      "Wenqi Zhang",
      "Xuhong Zhang"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "memory",
      "planning",
      "rag",
      "reasoning",
      "tool-use"
    ],
    "score": 20,
    "relevance": "high",
    "primary_query": "agent-memory",
    "matched_queries": [
      "agent-memory",
      "llm-agent"
    ]
  },
  {
    "id": "2607.20709",
    "arxiv_id": "2607.20709",
    "source": "arxiv",
    "source_id": "arxiv:2607.20709",
    "title": "NVIDIA-labs OO Agents: Native Python Object-Oriented Agents",
    "url": "https://arxiv.org/abs/2607.20709",
    "pdf_url": "https://arxiv.org/pdf/2607.20709",
    "published": "2026-07-22",
    "updated": "2026-07-22",
    "authors": [
      "Paul Furgale",
      "Severin Klingler",
      "James Nolan",
      "Matt Staats",
      "Gaia Di Lorenzo",
      "Elisa Martinez Abad",
      "Christian Schüller",
      "Razvan Dinu",
      "Alessio Devoto",
      "Pascal Berard",
      "Gal Kaplun",
      "Elad Sarafian",
      "Riccardo Roveri",
      "Leon Derczynski",
      "Ricardo Silveira Cabral"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "memory",
      "rag",
      "reasoning",
      "tool-use",
      "workflow-agent"
    ],
    "score": 20,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent",
      "coding-agent"
    ]
  },
  {
    "id": "2607.18039",
    "arxiv_id": "2607.18039",
    "source": "arxiv",
    "source_id": "arxiv:2607.18039",
    "title": "Evidence-in-the-Loop: Trace-Driven Optimization for Customer-Service LLM Agents",
    "url": "https://arxiv.org/abs/2607.18039",
    "pdf_url": "https://arxiv.org/pdf/2607.18039",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Chunming Wu",
      "Dafei Qiu",
      "Congde Yuan",
      "Charles Quan",
      "Jun Wu",
      "Suipeng Li",
      "Mo Wu",
      "Gavin Xie",
      "Hope Chen",
      "Max Yao"
    ],
    "categories": [
      "cs.IR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "computer-use",
      "memory",
      "rag",
      "tool-use",
      "workflow-agent"
    ],
    "score": 20,
    "relevance": "high",
    "primary_query": "agentic-ai",
    "matched_queries": [
      "agentic-ai",
      "llm-agent",
      "rag-agent"
    ]
  },
  {
    "id": "2607.17545",
    "arxiv_id": "2607.17545",
    "source": "arxiv",
    "source_id": "arxiv:2607.17545",
    "title": "Retain or Consolidate? Budget-Dependent Operator Selection for Language Agent Memory",
    "url": "https://arxiv.org/abs/2607.17545",
    "pdf_url": "https://arxiv.org/pdf/2607.17545",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Qingcan Kang",
      "Mingyang Liu",
      "Shixiong Kai",
      "Kaichao Liang",
      "Zhentao Tang",
      "Yuqi Cui",
      "Tao Zhong",
      "Mingxuan Yuan"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "memory",
      "rag",
      "tool-use"
    ],
    "score": 20,
    "relevance": "high",
    "primary_query": "agent-memory",
    "matched_queries": [
      "agent-memory",
      "language-agent"
    ]
  },
  {
    "id": "2607.15660",
    "arxiv_id": "2607.15660",
    "source": "arxiv",
    "source_id": "arxiv:2607.15660",
    "title": "ToolVerse: Unlocking Massive Environments and Long-Horizon Tasks for Agentic Reinforcement Learning",
    "url": "https://arxiv.org/abs/2607.15660",
    "pdf_url": "https://arxiv.org/pdf/2607.15660",
    "published": "2026-07-17",
    "updated": "2026-07-17",
    "authors": [
      "Shuaiyu Zhou",
      "Fengpeng Yue",
      "Zengjie Hu",
      "Yuanzhe Shen",
      "Chenyang Zhang",
      "feng hong",
      "Cao Liu",
      "Ke Zeng"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "planning",
      "reasoning",
      "tool-use",
      "world-model"
    ],
    "score": 20,
    "relevance": "high",
    "primary_query": "agent-evaluation",
    "matched_queries": [
      "agent-evaluation",
      "llm-agent",
      "tool-use"
    ]
  },
  {
    "id": "2607.15079",
    "arxiv_id": "2607.15079",
    "source": "arxiv",
    "source_id": "arxiv:2607.15079",
    "title": "BrainPilot: Automating Brain Discovery with Agentic Research",
    "url": "https://arxiv.org/abs/2607.15079",
    "pdf_url": "https://arxiv.org/pdf/2607.15079",
    "published": "2026-07-17",
    "updated": "2026-07-17",
    "authors": [
      "Haoxuan Li",
      "Tianci Gao",
      "Jianhe Li",
      "Yang Fan",
      "Runze Shi",
      "Weiran Wang",
      "Tianxiang Zhao",
      "Zezhao Wu",
      "Xiaoyang Jiang",
      "Qihui Zhang",
      "Jia Li",
      "Xiao Xiao",
      "Kai Du",
      "Xiaoxuan Jia",
      "Chao Xie",
      "Lu Mi"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "multi-agent",
      "rag",
      "reasoning",
      "tool-use",
      "workflow-agent"
    ],
    "score": 20,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent",
      "tool-use"
    ]
  },
  {
    "id": "2607.14651",
    "arxiv_id": "2607.14651",
    "source": "arxiv",
    "source_id": "arxiv:2607.14651",
    "title": "MemPoison: Uncovering Persistent Memory Threats and Structural Blind Spots in LLM Agents",
    "url": "https://arxiv.org/abs/2607.14651",
    "pdf_url": "https://arxiv.org/pdf/2607.14651",
    "published": "2026-07-16",
    "updated": "2026-07-16",
    "authors": [
      "Jifeng Gao",
      "Kang Xia",
      "Yi Zhang",
      "Xiaobin Hong",
      "Mingkai Lin",
      "Xingshen Wei",
      "Wenzhong Li",
      "Sanglu Lu"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "memory",
      "rag",
      "tool-use"
    ],
    "score": 20,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent"
    ]
  },
  {
    "id": "2607.08448",
    "arxiv_id": "2607.08448",
    "source": "arxiv",
    "source_id": "arxiv:2607.08448",
    "title": "Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents",
    "url": "https://arxiv.org/abs/2607.08448",
    "pdf_url": "https://arxiv.org/pdf/2607.08448",
    "published": "2026-07-15",
    "updated": "2026-07-15",
    "authors": [
      "Yixian Zhang",
      "Huanming Zhang",
      "Feng Gao",
      "Xiao Li",
      "Zhihao Liu",
      "Chunyang Zhu",
      "Jiaxing Qiu",
      "Yuchen Yan",
      "Jiyuan Liu",
      "Wenhao Tang",
      "Zhengru Fang",
      "Yi Nie",
      "Changxu Wei",
      "Yu Wang",
      "Wenbo Ding",
      "Chao Yu"
    ],
    "categories": [
      "cs.RO"
    ],
    "topics": [
      "coding-agent",
      "computer-use",
      "embodied-agent",
      "memory",
      "planning",
      "rag",
      "reasoning",
      "tool-use"
    ],
    "score": 20,
    "relevance": "high",
    "primary_query": "coding-agent",
    "matched_queries": [
      "coding-agent"
    ]
  },
  {
    "id": "2607.09653",
    "arxiv_id": "2607.09653",
    "source": "arxiv",
    "source_id": "arxiv:2607.09653",
    "title": "VEXAIoT: Autonomous IoT Vulnerability EXploitation using AI Agents",
    "url": "https://arxiv.org/abs/2607.09653",
    "pdf_url": "https://arxiv.org/pdf/2607.09653",
    "published": "2026-07-10",
    "updated": "2026-07-10",
    "authors": [
      "Katherine Swinea",
      "Kshitiz Aryal",
      "Lopamudra Praharaj",
      "Maanak Gupta"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "multi-agent",
      "planning",
      "rag",
      "reasoning",
      "tool-use",
      "workflow-agent"
    ],
    "score": 20,
    "relevance": "high",
    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm",
      "planning-agent"
    ]
  },
  {
    "id": "2607.22083",
    "arxiv_id": "2607.22083",
    "source": "arxiv",
    "source_id": "arxiv:2607.22083",
    "title": "Nanbeige4.2-3B: Unlocking Agentic Capabilities in a Compact Mode",
    "url": "https://arxiv.org/abs/2607.22083",
    "pdf_url": "https://arxiv.org/pdf/2607.22083",
    "published": "2026-07-24",
    "updated": "2026-07-24",
    "authors": [
      "Nanbeige Lab",
      ":",
      "Chen Yang",
      "Chengrui Huang",
      "Fufeng Lan",
      "Hanhui Chen",
      "Hao Zhou",
      "Huatong Song",
      "Jiaqi Cao",
      "Jiaying Zhu",
      "Jinlin Niu",
      "Kai Wang",
      "Lisheng Huang",
      "Qiliang Liang",
      "Ran Le",
      "Ruixiang Feng",
      "Shuang Sun",
      "Tao Gu",
      "Tao Zhang",
      "Tianyu Luo",
      "Yang Song",
      "Yun Xing",
      "Yuntao Wen",
      "Ziyao Xu",
      "Zongchao Chen",
      "et al. (1 additional authors not shown)"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "coding-agent",
      "planning",
      "reasoning",
      "tool-use",
      "workflow-agent"
    ],
    "score": 19,
    "relevance": "high",
    "primary_query": "agent-evaluation",
    "matched_queries": [
      "agent-evaluation",
      "coding-agent",
      "tool-use"
    ]
  },
  {
    "id": "2607.21920",
    "arxiv_id": "2607.21920",
    "source": "arxiv",
    "source_id": "arxiv:2607.21920",
    "title": "Systematic Literature Reviews With Two Multi-Agentic Systems And Human-In-The-Loop",
    "url": "https://arxiv.org/abs/2607.21920",
    "pdf_url": "https://arxiv.org/pdf/2607.21920",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Zexin Ren",
      "Zixuan Zhao",
      "Qiyun Li",
      "Yawen Wu",
      "Lanjing Wang",
      "Renjie Luo",
      "Yi Xu",
      "Qing Guo",
      "Jin Shi",
      "En Xie",
      "Feifang Hu",
      "Qian Shi"
    ],
    "categories": [
      "stat.AP"
    ],
    "topics": [
      "agent-evaluation",
      "multi-agent",
      "rag",
      "tool-use"
    ],
    "score": 19,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent",
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.20064",
    "arxiv_id": "2607.20064",
    "source": "arxiv",
    "source_id": "arxiv:2607.20064",
    "title": "PRO-LONG: Programmatic Memory Enables Long-Horizon Reasoning",
    "url": "https://arxiv.org/abs/2607.20064",
    "pdf_url": "https://arxiv.org/pdf/2607.20064",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Alexis Fox",
      "Junlin Wang",
      "Paul Rosu",
      "Bhuwan Dhingra"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "memory",
      "planning",
      "rag",
      "reasoning",
      "tool-use"
    ],
    "score": 19,
    "relevance": "high",
    "primary_query": "coding-agent",
    "matched_queries": [
      "coding-agent",
      "llm-agent"
    ]
  },
  {
    "id": "2607.20121",
    "arxiv_id": "2607.20121",
    "source": "arxiv",
    "source_id": "arxiv:2607.20121",
    "title": "OpenSkillRisk: Benchmarking Agent Safety When Using Real-World Risky Third-Party Skills",
    "url": "https://arxiv.org/abs/2607.20121",
    "pdf_url": "https://arxiv.org/pdf/2607.20121",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Qiyuan Liu",
      "Tingfeng Hui",
      "Kun Zhan",
      "Kaike Zhang",
      "Ning Miao"
    ],
    "categories": [
      "cs.CL"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "rag",
      "reasoning",
      "tool-use"
    ],
    "score": 19,
    "relevance": "high",
    "primary_query": "agent-safety",
    "matched_queries": [
      "agent-safety"
    ]
  },
  {
    "id": "2607.14573",
    "arxiv_id": "2607.14573",
    "source": "arxiv",
    "source_id": "arxiv:2607.14573",
    "title": "Alipay-PIBench: A Realistic Payment Integration Benchmark for Coding Agents",
    "url": "https://arxiv.org/abs/2607.14573",
    "pdf_url": "https://arxiv.org/pdf/2607.14573",
    "published": "2026-07-21",
    "updated": "2026-07-21",
    "authors": [
      "Shiyu Ying",
      "Xuejie Cao",
      "Yingfan Ma",
      "Yuanhao Dong",
      "Wenyu Chen",
      "Bowen Song",
      "Lin Zhu"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "coding-agent",
      "computer-use",
      "rag",
      "tool-use"
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    "score": 19,
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    "primary_query": "coding-agent",
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    "id": "2607.18485",
    "arxiv_id": "2607.18485",
    "source": "arxiv",
    "source_id": "arxiv:2607.18485",
    "title": "Trusted Credentials, Untrusted Behavior: Benchmarking LLM-Agent Security in High-Performance Computing",
    "url": "https://arxiv.org/abs/2607.18485",
    "pdf_url": "https://arxiv.org/pdf/2607.18485",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Jie Li"
    ],
    "categories": [
      "cs.CR"
    ],
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      "agent-evaluation",
      "agent-safety",
      "planning",
      "rag",
      "tool-use",
      "workflow-agent",
      "world-model"
    ],
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    "primary_query": "agent-safety",
    "matched_queries": [
      "agent-safety",
      "llm-agent",
      "planning-agent"
    ]
  },
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    "id": "2607.19430",
    "arxiv_id": "2607.19430",
    "source": "arxiv",
    "source_id": "arxiv:2607.19430",
    "title": "ChannelGuard: Safe Models Do Not Compose into Safe Multi-Agent Systems",
    "url": "https://arxiv.org/abs/2607.19430",
    "pdf_url": "https://arxiv.org/pdf/2607.19430",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Elias Hossain",
      "Md Mehedi Hasan Nipu",
      "Fatema Tuj Johora Faria",
      "Tasfia Nuzhat Ornee",
      "Maleeha Sheikh"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "memory",
      "multi-agent",
      "planning",
      "reasoning",
      "tool-use"
    ],
    "score": 19,
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    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
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    "id": "2607.17437",
    "arxiv_id": "2607.17437",
    "source": "arxiv",
    "source_id": "arxiv:2607.17437",
    "title": "Empirical Grounding Improves the Realism of LLM Agents Simulating Human Behavior During Disruptions",
    "url": "https://arxiv.org/abs/2607.17437",
    "pdf_url": "https://arxiv.org/pdf/2607.17437",
    "published": "2026-07-19",
    "updated": "2026-07-19",
    "authors": [
      "Chen Xia",
      "Zexi Kuang",
      "Yuqing Hu"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "memory",
      "planning",
      "rag",
      "reasoning",
      "world-model"
    ],
    "score": 19,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent",
      "planning-agent"
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    "id": "2607.15535",
    "arxiv_id": "2607.15535",
    "source": "arxiv",
    "source_id": "arxiv:2607.15535",
    "title": "Symbolic Predicate-Guided Language Agents for Inverse Design of Perovskite Oxides",
    "url": "https://arxiv.org/abs/2607.15535",
    "pdf_url": "https://arxiv.org/pdf/2607.15535",
    "published": "2026-07-16",
    "updated": "2026-07-16",
    "authors": [
      "Dong Hyeon Mok",
      "Seoin Back",
      "Victor Fung",
      "Guoxiang Hu"
    ],
    "categories": [
      "cond-mat.mtrl-sci"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "multi-agent",
      "rag",
      "reasoning"
    ],
    "score": 19,
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    "primary_query": "language-agent",
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      "llm-agent",
      "multi-agent-llm"
    ]
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    "id": "2607.14989",
    "arxiv_id": "2607.14989",
    "source": "arxiv",
    "source_id": "arxiv:2607.14989",
    "title": "OmniaBench: Benchmarking General AI Agents Across Diverse Scenarios",
    "url": "https://arxiv.org/abs/2607.14989",
    "pdf_url": "https://arxiv.org/pdf/2607.14989",
    "published": "2026-07-16",
    "updated": "2026-07-16",
    "authors": [
      "Chengyu Shen",
      "Yujie Fu",
      "Gangtao Xin",
      "Yanheng Hou",
      "Wenlong Fei",
      "Guojie Zhu",
      "Jiawei Li",
      "Hongcheng Gao",
      "Runming He",
      "Zhen Hao Wong",
      "Meiyi Qiang",
      "Hao Liang",
      "Zhao Cao",
      "Hao Jiang",
      "Chong Chen",
      "Wentao Zhang"
    ],
    "categories": [
      "cs.CL"
    ],
    "topics": [
      "agent-evaluation",
      "planning",
      "rag",
      "tool-use"
    ],
    "score": 19,
    "relevance": "high",
    "primary_query": "agent-evaluation",
    "matched_queries": [
      "agent-evaluation",
      "ai-agent"
    ]
  },
  {
    "id": "2607.13591",
    "arxiv_id": "2607.13591",
    "source": "arxiv",
    "source_id": "arxiv:2607.13591",
    "title": "Memory as a Controlled Process: Learned Adaptive Memory Management for LLM Agents",
    "url": "https://arxiv.org/abs/2607.13591",
    "pdf_url": "https://arxiv.org/pdf/2607.13591",
    "published": "2026-07-15",
    "updated": "2026-07-15",
    "authors": [
      "Eric Hanchen Jiang",
      "Zhi Zhang",
      "Yuchen Wu",
      "Levina Li",
      "Dong Liu",
      "Xiao Liang",
      "Rui Sun",
      "Yubei Li",
      "Edward Sun",
      "Haozheng Luo",
      "Zhaolu Kang",
      "Aylin Caliskan",
      "Kai-Wei Chang",
      "Ying Nian Wu"
    ],
    "categories": [
      "cs.CL"
    ],
    "topics": [
      "agent-evaluation",
      "memory",
      "planning",
      "rag"
    ],
    "score": 19,
    "relevance": "high",
    "primary_query": "planning-agent",
    "matched_queries": [
      "planning-agent"
    ]
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  {
    "id": "2607.06624",
    "arxiv_id": "2607.06624",
    "source": "arxiv",
    "source_id": "arxiv:2607.06624",
    "title": "AgentLens: Production-Assessed Trajectory Reviews for Coding Agent Evaluation",
    "url": "https://arxiv.org/abs/2607.06624",
    "pdf_url": "https://arxiv.org/pdf/2607.06624",
    "published": "2026-07-14",
    "updated": "2026-07-14",
    "authors": [
      "Andrey Podivilov",
      "Vadim Lomshakov",
      "Sergey Savin",
      "Matvei Startsev",
      "Roman Pozharskiy",
      "Maksim Parshin",
      "Sergey Nikolenko"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "planning",
      "tool-use"
    ],
    "score": 19,
    "relevance": "high",
    "primary_query": "agent-evaluation",
    "matched_queries": [
      "agent-evaluation",
      "coding-agent"
    ]
  },
  {
    "id": "2607.12267",
    "arxiv_id": "2607.12267",
    "source": "arxiv",
    "source_id": "arxiv:2607.12267",
    "title": "Track, Rank, Crack: Epistemic Working Memory Scales Multi-Hop Reasoning in Language Agents",
    "url": "https://arxiv.org/abs/2607.12267",
    "pdf_url": "https://arxiv.org/pdf/2607.12267",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Ning Liu"
    ],
    "categories": [
      "cs.LG"
    ],
    "topics": [
      "agent-evaluation",
      "memory",
      "rag",
      "reasoning",
      "tool-use"
    ],
    "score": 19,
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    "primary_query": "language-agent",
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      "language-agent",
      "tool-use"
    ]
  },
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    "id": "2607.20531",
    "arxiv_id": "2607.20531",
    "source": "arxiv",
    "source_id": "arxiv:2607.20531",
    "title": "DynamicMCPBench: A Trace-Grounded, Effect-Scored Benchmark for LLM Agents over Live MCP Servers",
    "url": "https://arxiv.org/abs/2607.20531",
    "pdf_url": "https://arxiv.org/pdf/2607.20531",
    "published": "2026-07-10",
    "updated": "2026-07-10",
    "authors": [
      "Jerzy Kamiński",
      "Ilya Galyukshev",
      "Artem Kuznetsov",
      "Sergey Chuprin",
      "Kirill Redko",
      "Aidar Shumbalov",
      "Anna Kalyuzhnaya"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "memory",
      "rag",
      "tool-use"
    ],
    "score": 19,
    "relevance": "high",
    "primary_query": "llm-agent",
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      "llm-agent",
      "tool-use"
    ]
  },
  {
    "id": "2607.08960",
    "arxiv_id": "2607.08960",
    "source": "arxiv",
    "source_id": "arxiv:2607.08960",
    "title": "Eluna: An Agentic LLM System for Automating Warehouse Operations with Reasoning and Task Execution",
    "url": "https://arxiv.org/abs/2607.08960",
    "pdf_url": "https://arxiv.org/pdf/2607.08960",
    "published": "2026-07-09",
    "updated": "2026-07-09",
    "authors": [
      "Ning Liu",
      "Kalle Kujanpää",
      "Zhaoxuan Zhu",
      "P Aditya Sreekar",
      "Kaiwen Liu",
      "Chuanneng Sun",
      "Jorge Marchena Menendez",
      "Matthew Bales",
      "Tianyu Yang",
      "Shahnawaz Alam",
      "Rose Yu",
      "Baoyuan Liu",
      "Kristina Klinkner",
      "Shervin Malmasi"
    ],
    "categories": [
      "cs.LG"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "memory",
      "multi-agent",
      "reasoning"
    ],
    "score": 19,
    "relevance": "high",
    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.22368",
    "arxiv_id": "2607.22368",
    "source": "arxiv",
    "source_id": "arxiv:2607.22368",
    "title": "Do Agent Benchmarks Measure Capability? Protocol Validity in the Age of Agentic AI",
    "url": "https://arxiv.org/abs/2607.22368",
    "pdf_url": "https://arxiv.org/pdf/2607.22368",
    "published": "2026-07-24",
    "updated": "2026-07-24",
    "authors": [
      "Jiaqi Shao",
      "Hanck Chen",
      "Wei Zhang",
      "Maxm Pan",
      "Bing Luo"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "planning",
      "tool-use"
    ],
    "score": 18,
    "relevance": "high",
    "primary_query": "agent-evaluation",
    "matched_queries": [
      "agent-evaluation",
      "agentic-ai"
    ]
  },
  {
    "id": "2607.21217",
    "arxiv_id": "2607.21217",
    "source": "arxiv",
    "source_id": "arxiv:2607.21217",
    "title": "ICAE-Bench: Evaluating Coding Agents as Interactive Project Builders",
    "url": "https://arxiv.org/abs/2607.21217",
    "pdf_url": "https://arxiv.org/pdf/2607.21217",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Zhongyuan Peng",
      "Dan Huang",
      "Chuyu Zhang",
      "Caijun Xu",
      "Changyi Xiao",
      "Shibo Hong",
      "David Lo",
      "Lin Qiu",
      "Xuezhi Cao",
      "Jiyuan He",
      "Yixin Cao"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "computer-use",
      "planning",
      "tool-use",
      "workflow-agent",
      "world-model"
    ],
    "score": 18,
    "relevance": "high",
    "primary_query": "coding-agent",
    "matched_queries": [
      "coding-agent",
      "tool-use"
    ]
  },
  {
    "id": "2607.20972",
    "arxiv_id": "2607.20972",
    "source": "arxiv",
    "source_id": "arxiv:2607.20972",
    "title": "Delivery, Not Storage: Cue-Anchored Working Memory as a Harness Property for Coding Agents",
    "url": "https://arxiv.org/abs/2607.20972",
    "pdf_url": "https://arxiv.org/pdf/2607.20972",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Swapnanil Saha"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "memory",
      "planning",
      "rag",
      "tool-use"
    ],
    "score": 18,
    "relevance": "high",
    "primary_query": "coding-agent",
    "matched_queries": [
      "coding-agent"
    ]
  },
  {
    "id": "2607.19913",
    "arxiv_id": "2607.19913",
    "source": "arxiv",
    "source_id": "arxiv:2607.19913",
    "title": "JANUS: Foreseeing Latent Risk for Long-Horizon Agent Safety",
    "url": "https://arxiv.org/abs/2607.19913",
    "pdf_url": "https://arxiv.org/pdf/2607.19913",
    "published": "2026-07-22",
    "updated": "2026-07-22",
    "authors": [
      "Yuan Xiong",
      "Linji Hao",
      "Shizhu He",
      "Yequan Wang",
      "Lijun Li"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "multi-agent",
      "planning",
      "rag",
      "tool-use",
      "world-model"
    ],
    "score": 18,
    "relevance": "high",
    "primary_query": "agent-safety",
    "matched_queries": [
      "agent-safety",
      "tool-use"
    ]
  },
  {
    "id": "2607.19595",
    "arxiv_id": "2607.19595",
    "source": "arxiv",
    "source_id": "arxiv:2607.19595",
    "title": "Twin Agent: Context Residual Compression for Privilege Separated Agents",
    "url": "https://arxiv.org/abs/2607.19595",
    "pdf_url": "https://arxiv.org/pdf/2607.19595",
    "published": "2026-07-21",
    "updated": "2026-07-21",
    "authors": [
      "Zhanhao Hu",
      "Dennis Jacob",
      "Xiao Huang",
      "Zhaorun Chen",
      "Bo Li",
      "David Wagner"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "coding-agent",
      "planning",
      "reasoning",
      "tool-use"
    ],
    "score": 18,
    "relevance": "high",
    "primary_query": "coding-agent",
    "matched_queries": [
      "coding-agent",
      "llm-agent",
      "tool-use"
    ]
  },
  {
    "id": "2607.18754",
    "arxiv_id": "2607.18754",
    "source": "arxiv",
    "source_id": "arxiv:2607.18754",
    "title": "AgentDebugX: An Open-Source Toolkit for Failure Observability, Attribution, and Recovery in LLM Agents",
    "url": "https://arxiv.org/abs/2607.18754",
    "pdf_url": "https://arxiv.org/pdf/2607.18754",
    "published": "2026-07-21",
    "updated": "2026-07-21",
    "authors": [
      "Kunlun Zhu",
      "Xuyan Ye",
      "Zhiguang Han",
      "Yuchen Zhao",
      "Bingxuan Li",
      "Weijia Zhang",
      "Muxin Tian",
      "Xiangru Tang",
      "Pan Lu",
      "James Zou",
      "Jiaxuan You",
      "Heng Ji"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "memory",
      "tool-use",
      "workflow-agent"
    ],
    "score": 18,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent"
    ]
  },
  {
    "id": "2607.17288",
    "arxiv_id": "2607.17288",
    "source": "arxiv",
    "source_id": "arxiv:2607.17288",
    "title": "SAGA: Synthetic Agentic Graph Architecture for Temporal Benchmark Generation",
    "url": "https://arxiv.org/abs/2607.17288",
    "pdf_url": "https://arxiv.org/pdf/2607.17288",
    "published": "2026-07-19",
    "updated": "2026-07-19",
    "authors": [
      "Jiacheng Ding",
      "Xiaofei Zhang"
    ],
    "categories": [
      "cs.DB"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "rag"
    ],
    "score": 18,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent",
      "rag-agent"
    ]
  },
  {
    "id": "2607.16851",
    "arxiv_id": "2607.16851",
    "source": "arxiv",
    "source_id": "arxiv:2607.16851",
    "title": "AgentBrew: Lifelong Knowledge Brewing from Strong Teachers to Weak LLM Agents",
    "url": "https://arxiv.org/abs/2607.16851",
    "pdf_url": "https://arxiv.org/pdf/2607.16851",
    "published": "2026-07-18",
    "updated": "2026-07-18",
    "authors": [
      "Yangqin Jiang",
      "Chao Huang"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "computer-use",
      "memory",
      "tool-use"
    ],
    "score": 18,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent",
      "tool-use"
    ]
  },
  {
    "id": "2607.15715",
    "arxiv_id": "2607.15715",
    "source": "arxiv",
    "source_id": "arxiv:2607.15715",
    "title": "Behavioral Controllability of Agentic Models for Information Extraction: From Fixed Workflows to Reflective Agents",
    "url": "https://arxiv.org/abs/2607.15715",
    "pdf_url": "https://arxiv.org/pdf/2607.15715",
    "published": "2026-07-17",
    "updated": "2026-07-17",
    "authors": [
      "Lujia Zhang",
      "Xingzhou Chen",
      "Hongwei Feng"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "memory",
      "rag",
      "reasoning",
      "tool-use",
      "workflow-agent"
    ],
    "score": 18,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent"
    ]
  },
  {
    "id": "2607.14277",
    "arxiv_id": "2607.14277",
    "source": "arxiv",
    "source_id": "arxiv:2607.14277",
    "title": "Multi-Head Latent Control: A Unified Interface for LLM Agent Decision Making",
    "url": "https://arxiv.org/abs/2607.14277",
    "pdf_url": "https://arxiv.org/pdf/2607.14277",
    "published": "2026-07-15",
    "updated": "2026-07-15",
    "authors": [
      "Amirhosein Ghasemabadi",
      "Ruichen Chen",
      "Bahador Rashidi",
      "Di Niu"
    ],
    "categories": [
      "cs.CL"
    ],
    "topics": [
      "agent-evaluation",
      "rag",
      "reasoning",
      "tool-use"
    ],
    "score": 18,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent",
      "tool-use"
    ]
  },
  {
    "id": "2607.14178",
    "arxiv_id": "2607.14178",
    "source": "arxiv",
    "source_id": "arxiv:2607.14178",
    "title": "ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System",
    "url": "https://arxiv.org/abs/2607.14178",
    "pdf_url": "https://arxiv.org/pdf/2607.14178",
    "published": "2026-07-15",
    "updated": "2026-07-15",
    "authors": [
      "Yutong He",
      "Daibo Li",
      "Guohong Li",
      "Jiahe Geng",
      "Zhengyang Huang",
      "Can Ren",
      "Zekun Zhang",
      "Yifan Liu",
      "Shuchen Zhu",
      "Hengrui Zhang",
      "Boao Kong",
      "Ming Sun",
      "Shu Li",
      "Chenyi Li",
      "Jiang Hu",
      "Kun Yuan",
      "Zaiwen Wen",
      "Pingwen Zhang"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "multi-agent",
      "rag",
      "reasoning"
    ],
    "score": 18,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent",
      "autonomous-agent-llm"
    ]
  },
  {
    "id": "2607.11751",
    "arxiv_id": "2607.11751",
    "source": "arxiv",
    "source_id": "arxiv:2607.11751",
    "title": "When Local Monitors Miss Compositional Harm: Diagnosing Distributed Backdoors in Multi-Agent Systems",
    "url": "https://arxiv.org/abs/2607.11751",
    "pdf_url": "https://arxiv.org/pdf/2607.11751",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Yibo Hu",
      "Ren Wang"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
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      "rag",
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      "multi-agent-llm",
      "tool-use"
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    "id": "2607.10608",
    "arxiv_id": "2607.10608",
    "source": "arxiv",
    "source_id": "arxiv:2607.10608",
    "title": "The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory",
    "url": "https://arxiv.org/abs/2607.10608",
    "pdf_url": "https://arxiv.org/pdf/2607.10608",
    "published": "2026-07-12",
    "updated": "2026-07-12",
    "authors": [
      "Yixiong Chen",
      "Xinyi Bai",
      "Alan Yuille"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "memory",
      "planning",
      "rag",
      "tool-use"
    ],
    "score": 18,
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    "primary_query": "ai-agent",
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      "ai-agent"
    ]
  },
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    "id": "2607.09101",
    "arxiv_id": "2607.09101",
    "source": "arxiv",
    "source_id": "arxiv:2607.09101",
    "title": "Multi-Agent LLM Collaboration for Unit Test Generation via Human-Testing-Inspired Workflows",
    "url": "https://arxiv.org/abs/2607.09101",
    "pdf_url": "https://arxiv.org/pdf/2607.09101",
    "published": "2026-07-10",
    "updated": "2026-07-10",
    "authors": [
      "Quanjun Zhang",
      "Ye Shang",
      "Siqi Gu",
      "Jianyi Zhou",
      "Chunrong Fang",
      "Zhenyu Chen",
      "Liang Xiao"
    ],
    "categories": [
      "cs.SE"
    ],
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      "agent-evaluation",
      "coding-agent",
      "multi-agent",
      "planning",
      "rag",
      "reasoning",
      "tool-use",
      "workflow-agent"
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    "primary_query": "multi-agent-llm",
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      "multi-agent-llm"
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    "id": "2607.08681",
    "arxiv_id": "2607.08681",
    "source": "arxiv",
    "source_id": "arxiv:2607.08681",
    "title": "SolarChain-Eval: A Physics-Constrained Benchmark for Trustworthy Economic Agents in Decentralized Energy Markets",
    "url": "https://arxiv.org/abs/2607.08681",
    "pdf_url": "https://arxiv.org/pdf/2607.08681",
    "published": "2026-07-09",
    "updated": "2026-07-09",
    "authors": [
      "Shilin Ou",
      "Yifan Xu",
      "Luyao Zhang"
    ],
    "categories": [
      "cs.AI"
    ],
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      "agent-evaluation",
      "agent-safety",
      "planning",
      "tool-use"
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    "score": 18,
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    "primary_query": "agent-evaluation",
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      "agent-evaluation",
      "agentic-ai",
      "autonomous-agent-llm"
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    "id": "2607.19653",
    "arxiv_id": "2607.19653",
    "source": "arxiv",
    "source_id": "arxiv:2607.19653",
    "title": "PerfAgent: Profiler-Guided Iterative Refinement for Repository-Level Code Optimization",
    "url": "https://arxiv.org/abs/2607.19653",
    "pdf_url": "https://arxiv.org/pdf/2607.19653",
    "published": "2026-07-21",
    "updated": "2026-07-21",
    "authors": [
      "Ryan Deng",
      "Yuanzhe Liu",
      "Bastian Lipka",
      "Yao Ma",
      "Xuhao Chen",
      "Tim Kaler",
      "Jatin Ganhotra"
    ],
    "categories": [
      "cs.SE"
    ],
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      "agent-evaluation",
      "coding-agent",
      "computer-use",
      "reasoning",
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      "workflow-agent"
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    "score": 17,
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    "primary_query": "coding-agent",
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      "coding-agent",
      "llm-agent"
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    "id": "2607.18659",
    "arxiv_id": "2607.18659",
    "source": "arxiv",
    "source_id": "arxiv:2607.18659",
    "title": "Broken Gates: Re-evaluating Web Bot Defenses in the Age of LLM Agents",
    "url": "https://arxiv.org/abs/2607.18659",
    "pdf_url": "https://arxiv.org/pdf/2607.18659",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Behzad Ousat",
      "Nikita Turkmen",
      "Lalchandra Rampersaud",
      "Dillan Bailey",
      "Amin Kharraz"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "computer-use",
      "tool-use",
      "workflow-agent"
    ],
    "score": 17,
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    "primary_query": "llm-agent",
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      "llm-agent",
      "web-gui-agent"
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    "id": "2607.19433",
    "arxiv_id": "2607.19433",
    "source": "arxiv",
    "source_id": "arxiv:2607.19433",
    "title": "The Chronos Vulnerability: A Taxonomy of Temporal Persistence and Memory-Based Deception in Agentic AI",
    "url": "https://arxiv.org/abs/2607.19433",
    "pdf_url": "https://arxiv.org/pdf/2607.19433",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Om Narayan",
      "Ramkinker Singh",
      "Praveen Baskar"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "memory",
      "planning",
      "workflow-agent"
    ],
    "score": 17,
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    "primary_query": "agentic-ai",
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      "agentic-ai"
    ]
  },
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    "id": "2607.12463",
    "arxiv_id": "2607.12463",
    "source": "arxiv",
    "source_id": "arxiv:2607.12463",
    "title": "Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models",
    "url": "https://arxiv.org/abs/2607.12463",
    "pdf_url": "https://arxiv.org/pdf/2607.12463",
    "published": "2026-07-19",
    "updated": "2026-07-19",
    "authors": [
      "Yubo Wang",
      "Jiarong Liang",
      "Yuxuan Zhang",
      "Xuye Liu",
      "Cong Wei",
      "Yuyu Zhang",
      "Ping Nie",
      "Wenhu Chen"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "reasoning",
      "tool-use"
    ],
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    "primary_query": "coding-agent",
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      "coding-agent",
      "function-calling",
      "tool-use"
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    "id": "2607.15246",
    "arxiv_id": "2607.15246",
    "source": "arxiv",
    "source_id": "arxiv:2607.15246",
    "title": "ARMOR++: Agentic Orchestration of a Multi-Domain Primitive Set for Transferable Attacks on Deepfake Detectors",
    "url": "https://arxiv.org/abs/2607.15246",
    "pdf_url": "https://arxiv.org/pdf/2607.15246",
    "published": "2026-07-16",
    "updated": "2026-07-16",
    "authors": [
      "Christos Korgialas",
      "Gabriel Lee Jun Rong",
      "Dion Jia Xu Ho",
      "Pai Chet Ng",
      "Xiaoxiao Miao",
      "Konstantinos N. Plataniotis"
    ],
    "categories": [
      "cs.CV"
    ],
    "topics": [
      "agent-evaluation",
      "multi-agent",
      "rag"
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    "primary_query": "agent-evaluation",
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      "agent-evaluation",
      "multi-agent-llm"
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    "id": "2606.31650",
    "arxiv_id": "2606.31650",
    "source": "arxiv",
    "source_id": "arxiv:2606.31650",
    "title": "ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL",
    "url": "https://arxiv.org/abs/2606.31650",
    "pdf_url": "https://arxiv.org/pdf/2606.31650",
    "published": "2026-07-14",
    "updated": "2026-07-14",
    "authors": [
      "Zijun Xie",
      "Binbin Zheng",
      "Enlei Gong",
      "Jihua Liu",
      "Yuyang You",
      "Lingfeng Liu",
      "Jiayao Tang",
      "Guanqun Zhao",
      "Aoqi Hu",
      "Zeyu Chen"
    ],
    "categories": [
      "cs.LG"
    ],
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      "agent-evaluation",
      "memory",
      "planning",
      "tool-use"
    ],
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    "primary_query": "language-agent",
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      "language-agent"
    ]
  },
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    "id": "2607.11141",
    "arxiv_id": "2607.11141",
    "source": "arxiv",
    "source_id": "arxiv:2607.11141",
    "title": "NextFund: A Unified Performance Tracking Platform for Agentic Portfolio Management",
    "url": "https://arxiv.org/abs/2607.11141",
    "pdf_url": "https://arxiv.org/pdf/2607.11141",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Changlun Li",
      "Peixian Ma",
      "Qiqi Duan",
      "Zhenyu Lin",
      "Peineng Wu"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "multi-agent",
      "tool-use"
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    "primary_query": "multi-agent-llm",
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      "multi-agent-llm"
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    "id": "2607.11042",
    "arxiv_id": "2607.11042",
    "source": "arxiv",
    "source_id": "arxiv:2607.11042",
    "title": "BackendForge: Benchmarking Agentic End-to-End Code Generation with Backend Services",
    "url": "https://arxiv.org/abs/2607.11042",
    "pdf_url": "https://arxiv.org/pdf/2607.11042",
    "published": "2026-07-12",
    "updated": "2026-07-12",
    "authors": [
      "Yuzhe Guo",
      "Mengzhou Wu",
      "Yuan Cao",
      "Jialei Wei",
      "Dezhi Ran",
      "Wei Yang",
      "Tao Xie"
    ],
    "categories": [
      "cs.SE"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "tool-use"
    ],
    "score": 17,
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    "primary_query": "coding-agent",
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      "coding-agent"
    ]
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    "id": "2607.10789",
    "arxiv_id": "2607.10789",
    "source": "arxiv",
    "source_id": "arxiv:2607.10789",
    "title": "Imaging-101: Benchmarking LLM Coding Agents on Scientific Computational Imaging",
    "url": "https://arxiv.org/abs/2607.10789",
    "pdf_url": "https://arxiv.org/pdf/2607.10789",
    "published": "2026-07-12",
    "updated": "2026-07-12",
    "authors": [
      "Siyi Chen",
      "Jiahe Ying",
      "Yixuan Jia",
      "Yuxuan Gu",
      "Enze Ye",
      "Weimin Bai",
      "Zhijun Zeng",
      "Shaochi Ren",
      "Binhong Gao",
      "Yubing Li",
      "Tianhan Zhang",
      "He Sun"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "planning"
    ],
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      "coding-agent"
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    "id": "2607.10582",
    "arxiv_id": "2607.10582",
    "source": "arxiv",
    "source_id": "arxiv:2607.10582",
    "title": "MemDecay: Region-Aware KV Cache Eviction for Efficient LLM Agent Inference",
    "url": "https://arxiv.org/abs/2607.10582",
    "pdf_url": "https://arxiv.org/pdf/2607.10582",
    "published": "2026-07-12",
    "updated": "2026-07-12",
    "authors": [
      "Venkatesha Matam",
      "Keon Kim"
    ],
    "categories": [
      "cs.LG"
    ],
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      "agent-evaluation",
      "coding-agent",
      "memory",
      "planning",
      "reasoning",
      "tool-use"
    ],
    "score": 17,
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    "primary_query": "planning-agent",
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      "planning-agent"
    ]
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    "id": "2606.29116",
    "arxiv_id": "2606.29116",
    "source": "arxiv",
    "source_id": "arxiv:2606.29116",
    "title": "Characterizing Large Language Model Agentic Workflows: A Study on N8n Ecosystem",
    "url": "https://arxiv.org/abs/2606.29116",
    "pdf_url": "https://arxiv.org/pdf/2606.29116",
    "published": "2026-07-11",
    "updated": "2026-07-11",
    "authors": [
      "Yutian Tang",
      "Yuming Zhou",
      "Huaming Chen"
    ],
    "categories": [
      "cs.AI"
    ],
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      "agent-safety",
      "planning",
      "rag",
      "tool-use",
      "workflow-agent"
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    "score": 17,
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    "primary_query": "planning-agent",
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      "planning-agent"
    ]
  },
  {
    "id": "2607.09195",
    "arxiv_id": "2607.09195",
    "source": "arxiv",
    "source_id": "arxiv:2607.09195",
    "title": "Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents",
    "url": "https://arxiv.org/abs/2607.09195",
    "pdf_url": "https://arxiv.org/pdf/2607.09195",
    "published": "2026-07-10",
    "updated": "2026-07-10",
    "authors": [
      "Izumi Takahara",
      "Teruyasu Mizoguchi"
    ],
    "categories": [
      "cs.AI"
    ],
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      "agent-evaluation",
      "planning",
      "reasoning",
      "tool-use"
    ],
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    "primary_query": "planning-agent",
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      "planning-agent",
      "tool-use"
    ]
  },
  {
    "id": "2607.09179",
    "arxiv_id": "2607.09179",
    "source": "arxiv",
    "source_id": "arxiv:2607.09179",
    "title": "Malaika: Understanding Malware through Tri-Grounded Agentic Reasoning",
    "url": "https://arxiv.org/abs/2607.09179",
    "pdf_url": "https://arxiv.org/pdf/2607.09179",
    "published": "2026-07-10",
    "updated": "2026-07-10",
    "authors": [
      "Xingzhi Qian",
      "Xinran Zheng",
      "Yiling He",
      "Lorenzo Cavallaro"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "multi-agent",
      "rag",
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      "tool-use"
    ],
    "score": 17,
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    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.09153",
    "arxiv_id": "2607.09153",
    "source": "arxiv",
    "source_id": "arxiv:2607.09153",
    "title": "KV-PRM: Efficient Process Reward Modeling via KV-Cache Transfer for Multi-Agent Test-Time Scaling",
    "url": "https://arxiv.org/abs/2607.09153",
    "pdf_url": "https://arxiv.org/pdf/2607.09153",
    "published": "2026-07-10",
    "updated": "2026-07-10",
    "authors": [
      "Peng Kuang",
      "Haibo Jin",
      "Xiaoyu Han",
      "Yanli Wang",
      "Xiaopeng Yuan",
      "Ye Yu",
      "Kaidi Xu",
      "Haohan Wang"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "computer-use",
      "memory",
      "multi-agent"
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    "score": 17,
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    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.08282",
    "arxiv_id": "2607.08282",
    "source": "arxiv",
    "source_id": "arxiv:2607.08282",
    "title": "Multi-Agent Firewall Architecture for Privacy Protection of Sensitive Data in Interactions with Language Models",
    "url": "https://arxiv.org/abs/2607.08282",
    "pdf_url": "https://arxiv.org/pdf/2607.08282",
    "published": "2026-07-09",
    "updated": "2026-07-09",
    "authors": [
      "Hugo García Cuesta",
      "Pablo Mateo Torrejón",
      "Alfonso Sánchez-Macián"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "computer-use",
      "multi-agent",
      "tool-use",
      "workflow-agent"
    ],
    "score": 17,
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    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.22520",
    "arxiv_id": "2607.22520",
    "source": "arxiv",
    "source_id": "arxiv:2607.22520",
    "title": "The Regression Tax: Decomposing Why Skills Help and Hurt LLM Agents",
    "url": "https://arxiv.org/abs/2607.22520",
    "pdf_url": "https://arxiv.org/pdf/2607.22520",
    "published": "2026-07-24",
    "updated": "2026-07-24",
    "authors": [
      "Darshan Tank",
      "Baran Nama"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "rag",
      "workflow-agent"
    ],
    "score": 16,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent"
    ]
  },
  {
    "id": "2607.22465",
    "arxiv_id": "2607.22465",
    "source": "arxiv",
    "source_id": "arxiv:2607.22465",
    "title": "TRACE-ROUTER: Task-Consistent and Adaptive Online Routing for Agentic AI",
    "url": "https://arxiv.org/abs/2607.22465",
    "pdf_url": "https://arxiv.org/pdf/2607.22465",
    "published": "2026-07-24",
    "updated": "2026-07-24",
    "authors": [
      "Ritik Raj",
      "Souvik Kundu",
      "Sarbartha Banerjee",
      "Dheemanth Joshi",
      "Ishita Vohra",
      "Tushar Krishna"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "planning",
      "rag",
      "workflow-agent"
    ],
    "score": 16,
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    "primary_query": "agent-evaluation",
    "matched_queries": [
      "agent-evaluation",
      "agentic-ai"
    ]
  },
  {
    "id": "2607.21835",
    "arxiv_id": "2607.21835",
    "source": "arxiv",
    "source_id": "arxiv:2607.21835",
    "title": "ToolGuardian: Declarative Security for AI Agent-Tool Interactions",
    "url": "https://arxiv.org/abs/2607.21835",
    "pdf_url": "https://arxiv.org/pdf/2607.21835",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Arun Ravindran",
      "Saurabh Deochake"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "reasoning",
      "tool-use"
    ],
    "score": 16,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent",
      "llm-agent"
    ]
  },
  {
    "id": "2607.21419",
    "arxiv_id": "2607.21419",
    "source": "arxiv",
    "source_id": "arxiv:2607.21419",
    "title": "PATS: Policy-Aware Training Scaffolding for Agentic Reinforcement Learning",
    "url": "https://arxiv.org/abs/2607.21419",
    "pdf_url": "https://arxiv.org/pdf/2607.21419",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Yipeng Shi",
      "Zhipeng Ma",
      "Yue Wang",
      "Qitai Tan",
      "Yang Li",
      "Peng Chen",
      "Zhengzhou Zhu"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "planning"
    ],
    "score": 16,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent"
    ]
  },
  {
    "id": "2607.21125",
    "arxiv_id": "2607.21125",
    "source": "arxiv",
    "source_id": "arxiv:2607.21125",
    "title": "Causal-AgentIR: Self-Evolving Causal Memory for Adaptive Image Restoration Agents",
    "url": "https://arxiv.org/abs/2607.21125",
    "pdf_url": "https://arxiv.org/pdf/2607.21125",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Hu Gao",
      "Yulong Chen",
      "Lizhuang Ma"
    ],
    "categories": [
      "cs.CV"
    ],
    "topics": [
      "agent-evaluation",
      "memory",
      "multi-agent",
      "planning",
      "rag",
      "reasoning",
      "tool-use"
    ],
    "score": 16,
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    "primary_query": "tool-use",
    "matched_queries": [
      "tool-use"
    ]
  },
  {
    "id": "2607.21832",
    "arxiv_id": "2607.21832",
    "source": "arxiv",
    "source_id": "arxiv:2607.21832",
    "title": "How Do AI Coding Agents Contribute to Software Development? an Empirical Study of Agentic Pull Requests",
    "url": "https://arxiv.org/abs/2607.21832",
    "pdf_url": "https://arxiv.org/pdf/2607.21832",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Iren Mazloomzadeh",
      "Mohammad Mehdi Morovati",
      "Foutse Khomh"
    ],
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      "cs.SE"
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      "coding-agent",
      "tool-use",
      "workflow-agent"
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    "primary_query": "coding-agent",
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    "id": "2607.19605",
    "arxiv_id": "2607.19605",
    "source": "arxiv",
    "source_id": "arxiv:2607.19605",
    "title": "RIME: Enabling Large-Scale Agentic Music Post-Production",
    "url": "https://arxiv.org/abs/2607.19605",
    "pdf_url": "https://arxiv.org/pdf/2607.19605",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Noah Schaffer",
      "Nikhil Singh"
    ],
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      "cs.SD"
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      "agent-evaluation",
      "coding-agent",
      "rag",
      "tool-use",
      "workflow-agent"
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    "primary_query": "coding-agent",
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    "id": "2607.21912",
    "arxiv_id": "2607.21912",
    "source": "arxiv",
    "source_id": "arxiv:2607.21912",
    "title": "Reliability-Contagion Feasibility in LLM Multi-Agent Networks",
    "url": "https://arxiv.org/abs/2607.21912",
    "pdf_url": "https://arxiv.org/pdf/2607.21912",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Ruiwu Niu",
      "Xincheng Shu",
      "Ying Zhao"
    ],
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      "cs.MA"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "multi-agent",
      "tool-use",
      "world-model"
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    "primary_query": "multi-agent-llm",
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      "multi-agent-llm"
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    "id": "2607.19837",
    "arxiv_id": "2607.19837",
    "source": "arxiv",
    "source_id": "arxiv:2607.19837",
    "title": "Know Your Agent: Reconnaissance-Driven Pentesting of AI Agents",
    "url": "https://arxiv.org/abs/2607.19837",
    "pdf_url": "https://arxiv.org/pdf/2607.19837",
    "published": "2026-07-22",
    "updated": "2026-07-22",
    "authors": [
      "Or Zion Eliav",
      "Eyal Lenga",
      "Shir Bernstien",
      "Yisroel Mirsky"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "coding-agent",
      "rag"
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    "score": 16,
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    "primary_query": "agent-safety",
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      "agent-safety",
      "ai-agent",
      "coding-agent"
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    "id": "2607.19336",
    "arxiv_id": "2607.19336",
    "source": "arxiv",
    "source_id": "arxiv:2607.19336",
    "title": "Agents in the Wild: Where Research Meets Deployment",
    "url": "https://arxiv.org/abs/2607.19336",
    "pdf_url": "https://arxiv.org/pdf/2607.19336",
    "published": "2026-07-21",
    "updated": "2026-07-21",
    "authors": [
      "Grace Hui Yang",
      "Pranav N. Venkit",
      "Hooman Sedghamiz",
      "Enrico Santus",
      "Victor Dibia",
      "Ioana Baldini"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "coding-agent",
      "planning",
      "reasoning",
      "tool-use"
    ],
    "score": 16,
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    "primary_query": "multi-agent-llm",
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      "multi-agent-llm"
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    "id": "2607.18847",
    "arxiv_id": "2607.18847",
    "source": "arxiv",
    "source_id": "arxiv:2607.18847",
    "title": "Data Leakage Prevention in Agentic Applications via Preemptive Hardening",
    "url": "https://arxiv.org/abs/2607.18847",
    "pdf_url": "https://arxiv.org/pdf/2607.18847",
    "published": "2026-07-21",
    "updated": "2026-07-21",
    "authors": [
      "Akansha Shukla",
      "Emily Bellov",
      "Parth Atulbhai Gandhi",
      "Yuval Elovici",
      "Asaf Shabtai"
    ],
    "categories": [
      "cs.CR"
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    "topics": [
      "agent-evaluation",
      "agent-safety",
      "planning",
      "tool-use",
      "workflow-agent"
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    "primary_query": "multi-agent-llm",
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      "multi-agent-llm"
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    "id": "2607.18575",
    "arxiv_id": "2607.18575",
    "source": "arxiv",
    "source_id": "arxiv:2607.18575",
    "title": "RECEIPT: Deterministic, Reward-Hacking-Resistant Verification for White-Box Agentic XSS Discovery",
    "url": "https://arxiv.org/abs/2607.18575",
    "pdf_url": "https://arxiv.org/pdf/2607.18575",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Muxi Lyu",
      "Karen Shieh",
      "Yiwei Hou",
      "Hao Wang",
      "Koushik Sen",
      "David Wagner"
    ],
    "categories": [
      "cs.CR"
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    "topics": [
      "agent-evaluation",
      "coding-agent",
      "computer-use",
      "planning",
      "reasoning"
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    "score": 16,
    "relevance": "high",
    "primary_query": "coding-agent",
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      "coding-agent"
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    "id": "2607.17050",
    "arxiv_id": "2607.17050",
    "source": "arxiv",
    "source_id": "arxiv:2607.17050",
    "title": "EvoGUI: An Evolution-Aware Benchmark for GUI State-Transition Understanding",
    "url": "https://arxiv.org/abs/2607.17050",
    "pdf_url": "https://arxiv.org/pdf/2607.17050",
    "published": "2026-07-18",
    "updated": "2026-07-18",
    "authors": [
      "Yaohan Yang",
      "Minglei Shi",
      "Borui Zhang",
      "Jie Zhou",
      "Jiwen Lu"
    ],
    "categories": [
      "cs.CV"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "planning",
      "rag",
      "tool-use"
    ],
    "score": 16,
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    "primary_query": "agent-evaluation",
    "matched_queries": [
      "agent-evaluation",
      "web-gui-agent"
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  {
    "id": "2607.16610",
    "arxiv_id": "2607.16610",
    "source": "arxiv",
    "source_id": "arxiv:2607.16610",
    "title": "Just A Rather Very Intelligent Spoken Agent",
    "url": "https://arxiv.org/abs/2607.16610",
    "pdf_url": "https://arxiv.org/pdf/2607.16610",
    "published": "2026-07-17",
    "updated": "2026-07-17",
    "authors": [
      "Chen Chen",
      "Zhehuai Chen"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "multi-agent",
      "planning",
      "tool-use",
      "workflow-agent"
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    "score": 16,
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    "primary_query": "agentic-ai",
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      "agentic-ai",
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    "id": "2607.15263",
    "arxiv_id": "2607.15263",
    "source": "arxiv",
    "source_id": "arxiv:2607.15263",
    "title": "Beyond Success Rate: Cost-Aware Evaluation of Offensive and Defensive Security Agents",
    "url": "https://arxiv.org/abs/2607.15263",
    "pdf_url": "https://arxiv.org/pdf/2607.15263",
    "published": "2026-07-17",
    "updated": "2026-07-17",
    "authors": [
      "Paul Kassianik",
      "Blaine Nelson",
      "Yaron Singer"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "embodied-agent",
      "reasoning",
      "tool-use"
    ],
    "score": 16,
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    "primary_query": "agent-evaluation",
    "matched_queries": [
      "agent-evaluation",
      "tool-use"
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    "id": "2607.15367",
    "arxiv_id": "2607.15367",
    "source": "arxiv",
    "source_id": "arxiv:2607.15367",
    "title": "AnovaX: A Local, Multi-Agent Voice Assistant with LLM Planning, Typed Executors, and Adaptive Recovery",
    "url": "https://arxiv.org/abs/2607.15367",
    "pdf_url": "https://arxiv.org/pdf/2607.15367",
    "published": "2026-07-16",
    "updated": "2026-07-16",
    "authors": [
      "Raunak B Sinha"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-safety",
      "computer-use",
      "multi-agent",
      "planning",
      "rag",
      "tool-use"
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    "score": 16,
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    "primary_query": "multi-agent-llm",
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      "multi-agent-llm"
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    "id": "2607.14165",
    "arxiv_id": "2607.14165",
    "source": "arxiv",
    "source_id": "arxiv:2607.14165",
    "title": "Towards Reliable AI-Assisted Analog Design: Template-Constrained LLM Agents for SAR ADC Generation",
    "url": "https://arxiv.org/abs/2607.14165",
    "pdf_url": "https://arxiv.org/pdf/2607.14165",
    "published": "2026-07-15",
    "updated": "2026-07-15",
    "authors": [
      "Dimple Vijay Kochar",
      "Hae-Seung Lee",
      "Anantha P. Chandrakasan"
    ],
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      "cs.SE"
    ],
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      "planning",
      "rag",
      "workflow-agent",
      "world-model"
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    "primary_query": "llm-agent",
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    "id": "2606.05711",
    "arxiv_id": "2606.05711",
    "source": "arxiv",
    "source_id": "arxiv:2606.05711",
    "title": "Beyond tokens: a unified framework for latent communication in LLM-based multi-agent systems",
    "url": "https://arxiv.org/abs/2606.05711",
    "pdf_url": "https://arxiv.org/pdf/2606.05711",
    "published": "2026-07-15",
    "updated": "2026-07-15",
    "authors": [
      "Yingzhuo Liu"
    ],
    "categories": [
      "cs.CL"
    ],
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      "agent-safety",
      "computer-use",
      "multi-agent",
      "planning",
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      "tool-use"
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    "score": 16,
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    "primary_query": "language-agent",
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    "id": "2607.12406",
    "arxiv_id": "2607.12406",
    "source": "arxiv",
    "source_id": "arxiv:2607.12406",
    "title": "Isolation as a First-Class Principle for LLM-Agent System Safety: Concepts, Taxonomy, Challenges and Future Directions",
    "url": "https://arxiv.org/abs/2607.12406",
    "pdf_url": "https://arxiv.org/pdf/2607.12406",
    "published": "2026-07-14",
    "updated": "2026-07-14",
    "authors": [
      "Huihao Jing",
      "Wenbin Hu",
      "Shaojin Chen",
      "Haochen Shi",
      "Sirui Zhang",
      "Hanyu Yang",
      "Changxuan Fan",
      "Zhongwei Xie",
      "Hongyu Luo",
      "Wun Yu Chan",
      "Wei Fan",
      "Haoran Li",
      "Yangqiu Song"
    ],
    "categories": [
      "cs.AI"
    ],
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      "agent-evaluation",
      "agent-safety",
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      "rag",
      "tool-use",
      "workflow-agent"
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    "primary_query": "agentic-ai",
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    "id": "2607.13081",
    "arxiv_id": "2607.13081",
    "source": "arxiv",
    "source_id": "arxiv:2607.13081",
    "title": "SingGuard-NSFA: Extensible Guardrails for Agentic AI via Generative Reasoning and Real-Time Classification",
    "url": "https://arxiv.org/abs/2607.13081",
    "pdf_url": "https://arxiv.org/pdf/2607.13081",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "SingGuard Team"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "computer-use",
      "reasoning",
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    "primary_query": "agent-safety",
    "matched_queries": [
      "agent-safety",
      "agentic-ai"
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  {
    "id": "2607.13085",
    "arxiv_id": "2607.13085",
    "source": "arxiv",
    "source_id": "arxiv:2607.13085",
    "title": "Baselines Before Architecture: Evaluating Coding Agents for Autonomous Penetration Testing",
    "url": "https://arxiv.org/abs/2607.13085",
    "pdf_url": "https://arxiv.org/pdf/2607.13085",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Ananda Dhakal",
      "Krish Neupane",
      "Aarjan Chaudhary"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "coding-agent",
      "rag"
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    "primary_query": "coding-agent",
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      "coding-agent"
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  {
    "id": "2607.08894",
    "arxiv_id": "2607.08894",
    "source": "arxiv",
    "source_id": "arxiv:2607.08894",
    "title": "GATS: Graph-Augmented Tree Search with Layered World Models for Efficient Agent Planning",
    "url": "https://arxiv.org/abs/2607.08894",
    "pdf_url": "https://arxiv.org/pdf/2607.08894",
    "published": "2026-07-09",
    "updated": "2026-07-09",
    "authors": [
      "Maureese Williams",
      "Dymitr Nowicki"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "coding-agent",
      "computer-use",
      "embodied-agent",
      "planning",
      "tool-use",
      "workflow-agent",
      "world-model"
    ],
    "score": 16,
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    "primary_query": "language-agent",
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      "language-agent",
      "planning-agent"
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    "id": "2607.19215",
    "arxiv_id": "2607.19215",
    "source": "arxiv",
    "source_id": "arxiv:2607.19215",
    "title": "HACO: Hedged Agent Computing for Reliable LLM Systems",
    "url": "https://arxiv.org/abs/2607.19215",
    "pdf_url": "https://arxiv.org/pdf/2607.19215",
    "published": "2026-07-21",
    "updated": "2026-07-21",
    "authors": [
      "Enhan Li",
      "Hongyang Du"
    ],
    "categories": [
      "cs.NI"
    ],
    "topics": [
      "agent-evaluation",
      "memory",
      "tool-use",
      "workflow-agent"
    ],
    "score": 15,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent",
      "tool-use"
    ]
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  {
    "id": "2605.28787",
    "arxiv_id": "2605.28787",
    "source": "arxiv",
    "source_id": "arxiv:2605.28787",
    "title": "Do Data Agents Need Semantic Metadata? A Comparative Study in Agentic Data Retrieval",
    "url": "https://arxiv.org/abs/2605.28787",
    "pdf_url": "https://arxiv.org/pdf/2605.28787",
    "published": "2026-07-21",
    "updated": "2026-07-21",
    "authors": [
      "Shiyu Chen",
      "Tarfah Alrashed",
      "Alon Halevy",
      "Natasha Noy"
    ],
    "categories": [
      "cs.IR"
    ],
    "topics": [
      "agent-evaluation",
      "rag",
      "tool-use",
      "workflow-agent"
    ],
    "score": 15,
    "relevance": "high",
    "primary_query": "autonomous-agent-llm",
    "matched_queries": [
      "autonomous-agent-llm"
    ]
  },
  {
    "id": "2607.18064",
    "arxiv_id": "2607.18064",
    "source": "arxiv",
    "source_id": "arxiv:2607.18064",
    "title": "Autoresearch with Coding Agents: Generalizers and Metric-Maximizers on Quran Recitation Data",
    "url": "https://arxiv.org/abs/2607.18064",
    "pdf_url": "https://arxiv.org/pdf/2607.18064",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Nursultan Askarbekuly",
      "Mohamad Al Mdfaa",
      "Ahmed Helaly",
      "Gonzalo Ferrer",
      "Manuel Mazzara"
    ],
    "categories": [
      "cs.SE"
    ],
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      "agent-evaluation",
      "agent-safety",
      "coding-agent",
      "memory",
      "reasoning"
    ],
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    "primary_query": "coding-agent",
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      "coding-agent"
    ]
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  {
    "id": "2607.05690",
    "arxiv_id": "2607.05690",
    "source": "arxiv",
    "source_id": "arxiv:2607.05690",
    "title": "Memory in the Loop: In-Process Retrieval as Extended Working Memory for Language Agents",
    "url": "https://arxiv.org/abs/2607.05690",
    "pdf_url": "https://arxiv.org/pdf/2607.05690",
    "published": "2026-07-19",
    "updated": "2026-07-19",
    "authors": [
      "Yusuf Khan",
      "Carlo Lipizzi"
    ],
    "categories": [
      "cs.AI"
    ],
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      "agent-evaluation",
      "memory",
      "rag",
      "tool-use"
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    "primary_query": "language-agent",
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    "id": "2607.15593",
    "arxiv_id": "2607.15593",
    "source": "arxiv",
    "source_id": "arxiv:2607.15593",
    "title": "Scalable LLM Agent Tool Access in the Cloud",
    "url": "https://arxiv.org/abs/2607.15593",
    "pdf_url": "https://arxiv.org/pdf/2607.15593",
    "published": "2026-07-16",
    "updated": "2026-07-16",
    "authors": [
      "Mingxin Li",
      "Enge Song",
      "Yueshang Zuo",
      "Xiaodong Liu",
      "Rong Wen",
      "Qiang Fu",
      "Gianni Antichi",
      "Jian He",
      "Jing Tie",
      "Zhou Shao",
      "Xiaobo Xue",
      "Xiong Xiao",
      "Luyao Zhong",
      "Shaokai Zhang",
      "Jiangu Zhao",
      "Jianyuan Lu",
      "Shize Zhang",
      "Xiaoqing Sun",
      "Changgang Zheng",
      "Zihao Fan",
      "Haonan Li",
      "Tian Pan",
      "Xiaomin Wu",
      "Yang Song",
      "Xing Li",
      "et al. (5 additional authors not shown)"
    ],
    "categories": [
      "cs.DC"
    ],
    "topics": [
      "agent-evaluation",
      "memory",
      "planning",
      "rag",
      "tool-use"
    ],
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    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent"
    ]
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  {
    "id": "2607.14777",
    "arxiv_id": "2607.14777",
    "source": "arxiv",
    "source_id": "arxiv:2607.14777",
    "title": "SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning",
    "url": "https://arxiv.org/abs/2607.14777",
    "pdf_url": "https://arxiv.org/pdf/2607.14777",
    "published": "2026-07-16",
    "updated": "2026-07-16",
    "authors": [
      "Jinyang Wu",
      "Shuo Yang",
      "Zhengxi Lu",
      "Fan Zhang",
      "Yuhao Shen",
      "Lang Feng",
      "Haoran Luo",
      "Zheng Lian",
      "Shuai Zhang",
      "Zhengqi Wen",
      "Jianhua Tao"
    ],
    "categories": [
      "cs.CL"
    ],
    "topics": [
      "computer-use",
      "planning",
      "tool-use",
      "workflow-agent"
    ],
    "score": 15,
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    "primary_query": "tool-use",
    "matched_queries": [
      "tool-use"
    ]
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  {
    "id": "2607.13987",
    "arxiv_id": "2607.13987",
    "source": "arxiv",
    "source_id": "arxiv:2607.13987",
    "title": "Agent Skill Security: Threat Models, Attacks, Defenses, and Evaluation",
    "url": "https://arxiv.org/abs/2607.13987",
    "pdf_url": "https://arxiv.org/pdf/2607.13987",
    "published": "2026-07-15",
    "updated": "2026-07-15",
    "authors": [
      "Sanket Badhe",
      "Priyanka Tiwari"
    ],
    "categories": [
      "cs.CR"
    ],
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      "agent-safety",
      "coding-agent",
      "planning",
      "rag"
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    "primary_query": "llm-agent",
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    ]
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    "id": "2607.14264",
    "arxiv_id": "2607.14264",
    "source": "arxiv",
    "source_id": "arxiv:2607.14264",
    "title": "MonteRET: AI Agent Enhancing Multimodal LLMs with Multi-granularity Knowledge Retrieval for Chest CT Report Generation",
    "url": "https://arxiv.org/abs/2607.14264",
    "pdf_url": "https://arxiv.org/pdf/2607.14264",
    "published": "2026-07-15",
    "updated": "2026-07-15",
    "authors": [
      "Yi Lin",
      "Yihao Ding",
      "Elana Benishay",
      "Elefterios Trikantzopoulos",
      "David Nauheim",
      "Hanley Ong",
      "Jiang Bian",
      "Hua Xu",
      "Yuzhe Yang",
      "George Shih",
      "Yifan Peng"
    ],
    "categories": [
      "cs.CV"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "computer-use",
      "rag"
    ],
    "score": 15,
    "relevance": "high",
    "primary_query": "ai-agent",
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      "ai-agent"
    ]
  },
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    "id": "2607.13854",
    "arxiv_id": "2607.13854",
    "source": "arxiv",
    "source_id": "arxiv:2607.13854",
    "title": "SPyCE: Skill-Policy Co-evolution for Multimodal Agents",
    "url": "https://arxiv.org/abs/2607.13854",
    "pdf_url": "https://arxiv.org/pdf/2607.13854",
    "published": "2026-07-15",
    "updated": "2026-07-15",
    "authors": [
      "Ru Zhang",
      "Weijie Qiu"
    ],
    "categories": [
      "cs.CL"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "memory",
      "rag",
      "reasoning",
      "tool-use",
      "workflow-agent"
    ],
    "score": 15,
    "relevance": "high",
    "primary_query": "tool-use",
    "matched_queries": [
      "tool-use"
    ]
  },
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    "id": "2607.13196",
    "arxiv_id": "2607.13196",
    "source": "arxiv",
    "source_id": "arxiv:2607.13196",
    "title": "From Human-Centric to Agentic Code Review: The Impact of Different Generations of Generative AI Technology on Review Quality",
    "url": "https://arxiv.org/abs/2607.13196",
    "pdf_url": "https://arxiv.org/pdf/2607.13196",
    "published": "2026-07-14",
    "updated": "2026-07-14",
    "authors": [
      "Suzhen Zhong",
      "Shayan Noei",
      "Bram Adams",
      "Ying Zou"
    ],
    "categories": [
      "cs.SE"
    ],
    "topics": [
      "computer-use",
      "multi-agent",
      "planning",
      "tool-use"
    ],
    "score": 15,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent"
    ]
  },
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    "id": "2607.12397",
    "arxiv_id": "2607.12397",
    "source": "arxiv",
    "source_id": "arxiv:2607.12397",
    "title": "Critic Experience Bank: Self-Evolving Step-Level Confidence Estimation for LLM Agents",
    "url": "https://arxiv.org/abs/2607.12397",
    "pdf_url": "https://arxiv.org/pdf/2607.12397",
    "published": "2026-07-14",
    "updated": "2026-07-14",
    "authors": [
      "Yaopei Zeng",
      "Congchao Wang",
      "JianHang Chen",
      "Nan Wang",
      "Yurui Chang",
      "Lu Lin"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "memory",
      "tool-use"
    ],
    "score": 15,
    "relevance": "high",
    "primary_query": "agent-evaluation",
    "matched_queries": [
      "agent-evaluation"
    ]
  },
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    "id": "2607.14145",
    "arxiv_id": "2607.14145",
    "source": "arxiv",
    "source_id": "arxiv:2607.14145",
    "title": "ToolAnchor: Anchoring Counterfactual Context to Boost Agentic Tool-use Capability",
    "url": "https://arxiv.org/abs/2607.14145",
    "pdf_url": "https://arxiv.org/pdf/2607.14145",
    "published": "2026-07-14",
    "updated": "2026-07-14",
    "authors": [
      "Weiting Liu",
      "Jieyi Bi",
      "Wanqi Zhou",
      "Jianfeng Feng",
      "Yining Ma",
      "Ai Han",
      "Wenlian Lu"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "planning",
      "reasoning",
      "tool-use"
    ],
    "score": 15,
    "relevance": "high",
    "primary_query": "tool-use",
    "matched_queries": [
      "tool-use"
    ]
  },
  {
    "id": "2607.12068",
    "arxiv_id": "2607.12068",
    "source": "arxiv",
    "source_id": "arxiv:2607.12068",
    "title": "Beyond Test Presence: Assessing the Quality and Robustness of Agent-Generated Tests in Open-Source Projects",
    "url": "https://arxiv.org/abs/2607.12068",
    "pdf_url": "https://arxiv.org/pdf/2607.12068",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Preet Jhanglani",
      "Zeel Kaushal Desai",
      "Vidhi Kansara",
      "Eman Abdullah AlOmar"
    ],
    "categories": [
      "cs.SE"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "coding-agent",
      "rag"
    ],
    "score": 15,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent",
      "coding-agent"
    ]
  },
  {
    "id": "2607.11250",
    "arxiv_id": "2607.11250",
    "source": "arxiv",
    "source_id": "arxiv:2607.11250",
    "title": "Multi-Agent LLMs Fail to Explore Each Other",
    "url": "https://arxiv.org/abs/2607.11250",
    "pdf_url": "https://arxiv.org/pdf/2607.11250",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Hyeong Kyu Choi",
      "Jiatong Li",
      "Wendi Li",
      "Xin Eric Wang",
      "Sharon Li"
    ],
    "categories": [
      "cs.MA"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "multi-agent",
      "tool-use"
    ],
    "score": 15,
    "relevance": "high",
    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.11046",
    "arxiv_id": "2607.11046",
    "source": "arxiv",
    "source_id": "arxiv:2607.11046",
    "title": "Retrieval-Oriented Code Representations in Agentic Bug Localization",
    "url": "https://arxiv.org/abs/2607.11046",
    "pdf_url": "https://arxiv.org/pdf/2607.11046",
    "published": "2026-07-12",
    "updated": "2026-07-12",
    "authors": [
      "Genevieve Caumartin",
      "Tse-Hsun",
      "Chen",
      "Diego Elias Costa"
    ],
    "categories": [
      "cs.SE"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "computer-use",
      "rag"
    ],
    "score": 15,
    "relevance": "high",
    "primary_query": "coding-agent",
    "matched_queries": [
      "coding-agent"
    ]
  },
  {
    "id": "2607.10490",
    "arxiv_id": "2607.10490",
    "source": "arxiv",
    "source_id": "arxiv:2607.10490",
    "title": "NetInjectBench: Benchmarking Indirect Prompt Injection in Tool-Using Large Language Model Agents for Network Operations",
    "url": "https://arxiv.org/abs/2607.10490",
    "pdf_url": "https://arxiv.org/pdf/2607.10490",
    "published": "2026-07-11",
    "updated": "2026-07-11",
    "authors": [
      "Ruksat Khan Shayoni",
      "Muhammad Faraz Shoaib",
      "S M Asif Hossain",
      "M. F. Mridha"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "tool-use"
    ],
    "score": 15,
    "relevance": "high",
    "primary_query": "tool-use",
    "matched_queries": [
      "tool-use"
    ]
  },
  {
    "id": "2607.10286",
    "arxiv_id": "2607.10286",
    "source": "arxiv",
    "source_id": "arxiv:2607.10286",
    "title": "Can Agentic Trading Systems Pay for Their Own Intelligence?",
    "url": "https://arxiv.org/abs/2607.10286",
    "pdf_url": "https://arxiv.org/pdf/2607.10286",
    "published": "2026-07-11",
    "updated": "2026-07-11",
    "authors": [
      "Qiqi Duan",
      "Changlun Li",
      "Chen Wang",
      "Fan Zhang",
      "Mengxiang Wang",
      "Dayi Miao",
      "Peixian Ma",
      "Jiangpeng Yan",
      "Liyuan Chen",
      "Shuoling Liu",
      "Preslav Nakov",
      "Yuyu Luo",
      "Nan Tang"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "reasoning",
      "tool-use"
    ],
    "score": 15,
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    "primary_query": "tool-use",
    "matched_queries": [
      "tool-use"
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  },
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    "id": "2607.07405",
    "arxiv_id": "2607.07405",
    "source": "arxiv",
    "source_id": "arxiv:2607.07405",
    "title": "Reason Less, Verify More: Deterministic Gates Recover a Silent Policy-Violation Failure Mode in Tool-Using LLM Agents",
    "url": "https://arxiv.org/abs/2607.07405",
    "pdf_url": "https://arxiv.org/pdf/2607.07405",
    "published": "2026-07-11",
    "updated": "2026-07-11",
    "authors": [
      "Vikas Reddy",
      "Sumanth Reddy Challaram",
      "Abhishek Basu"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "reasoning",
      "tool-use"
    ],
    "score": 15,
    "relevance": "high",
    "primary_query": "tool-use",
    "matched_queries": [
      "tool-use"
    ]
  },
  {
    "id": "2607.10463",
    "arxiv_id": "2607.10463",
    "source": "arxiv",
    "source_id": "arxiv:2607.10463",
    "title": "GRASP: GRanularity-Aware Search Policy for Agentic RAG",
    "url": "https://arxiv.org/abs/2607.10463",
    "pdf_url": "https://arxiv.org/pdf/2607.10463",
    "published": "2026-07-11",
    "updated": "2026-07-11",
    "authors": [
      "Varun Gandhi",
      "Jaewook Lee",
      "Shantanu Todmal",
      "Franck Dernoncourt",
      "Ryan Rossi",
      "Zichao Wang",
      "Andrew Lan"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "rag",
      "reasoning",
      "tool-use"
    ],
    "score": 15,
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    "primary_query": "rag-agent",
    "matched_queries": [
      "rag-agent"
    ]
  },
  {
    "id": "2607.09092",
    "arxiv_id": "2607.09092",
    "source": "arxiv",
    "source_id": "arxiv:2607.09092",
    "title": "AgentKGV: Agentic LLM-RAG Framework with Two-Stage Training for the Fact Verification of Knowledge Graphs",
    "url": "https://arxiv.org/abs/2607.09092",
    "pdf_url": "https://arxiv.org/pdf/2607.09092",
    "published": "2026-07-10",
    "updated": "2026-07-10",
    "authors": [
      "Yumin Heo",
      "Hyeon-gu Lee",
      "Sumin Seo",
      "Youngjoong Ko"
    ],
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      "cs.CL"
    ],
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      "agent-evaluation",
      "rag",
      "reasoning",
      "tool-use"
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    "relevance": "high",
    "primary_query": "rag-agent",
    "matched_queries": [
      "rag-agent"
    ]
  },
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    "id": "2607.09076",
    "arxiv_id": "2607.09076",
    "source": "arxiv",
    "source_id": "arxiv:2607.09076",
    "title": "Neuro-Agentic Control: A Deep Learning-based LLM-Powered Agentic AI Framework for Controlling Security Controls",
    "url": "https://arxiv.org/abs/2607.09076",
    "pdf_url": "https://arxiv.org/pdf/2607.09076",
    "published": "2026-07-09",
    "updated": "2026-07-09",
    "authors": [
      "Saroj Gopali",
      "Bipin Chhetri",
      "Deepika Giri",
      "Sima Siami-Namini",
      "Akbar Siami Namin"
    ],
    "categories": [
      "cs.AI"
    ],
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      "agent-evaluation",
      "agent-safety",
      "planning",
      "reasoning",
      "tool-use"
    ],
    "score": 15,
    "relevance": "high",
    "primary_query": "agentic-ai",
    "matched_queries": [
      "agentic-ai"
    ]
  },
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    "id": "2607.08180",
    "arxiv_id": "2607.08180",
    "source": "arxiv",
    "source_id": "arxiv:2607.08180",
    "title": "Out of Sight: Compression-Aware Content Protection against Agentic Crawlers",
    "url": "https://arxiv.org/abs/2607.08180",
    "pdf_url": "https://arxiv.org/pdf/2607.08180",
    "published": "2026-07-09",
    "updated": "2026-07-09",
    "authors": [
      "Xuefei Wang"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "computer-use",
      "memory",
      "reasoning",
      "workflow-agent"
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    "score": 15,
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    "primary_query": "agentic-ai",
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      "agentic-ai"
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  {
    "id": "2607.22443",
    "arxiv_id": "2607.22443",
    "source": "arxiv",
    "source_id": "arxiv:2607.22443",
    "title": "A Human-Augmenting Agentic Workflow for Observational Causal Inference",
    "url": "https://arxiv.org/abs/2607.22443",
    "pdf_url": "https://arxiv.org/pdf/2607.22443",
    "published": "2026-07-24",
    "updated": "2026-07-24",
    "authors": [
      "Winston Chou",
      "Adrien Alexandre",
      "Lars Olds",
      "Yi Zhang",
      "Nathan Kallus"
    ],
    "categories": [
      "stat.CO"
    ],
    "topics": [
      "agent-evaluation",
      "rag",
      "tool-use",
      "workflow-agent"
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    "score": 14,
    "relevance": "high",
    "primary_query": "agentic-ai",
    "matched_queries": [
      "agentic-ai"
    ]
  },
  {
    "id": "2607.21273",
    "arxiv_id": "2607.21273",
    "source": "arxiv",
    "source_id": "arxiv:2607.21273",
    "title": "The Dark Room in the Reward Channel: Dense Prediction Rewards Collapse GRPO-Trained LLM Agents -- and What Actually Works",
    "url": "https://arxiv.org/abs/2607.21273",
    "pdf_url": "https://arxiv.org/pdf/2607.21273",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Yu Wang"
    ],
    "categories": [
      "cs.LG"
    ],
    "topics": [
      "memory",
      "planning",
      "tool-use"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "llm-agent",
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      "llm-agent"
    ]
  },
  {
    "id": "2607.15557",
    "arxiv_id": "2607.15557",
    "source": "arxiv",
    "source_id": "arxiv:2607.15557",
    "title": "SkillCorpus: Consolidating and Evaluating the Open Skill Ecosystem for Real-World LLM Agents",
    "url": "https://arxiv.org/abs/2607.15557",
    "pdf_url": "https://arxiv.org/pdf/2607.15557",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Yanze Wang",
      "Pengfei Yao",
      "Tianyi Sun",
      "Chuanrui Hu",
      "Yan Xiao",
      "Yunyun Han",
      "Yifan Chen",
      "Jun Sun",
      "Yafeng Deng"
    ],
    "categories": [
      "cs.CL"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "rag"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent"
    ]
  },
  {
    "id": "2607.20827",
    "arxiv_id": "2607.20827",
    "source": "arxiv",
    "source_id": "arxiv:2607.20827",
    "title": "Auditing Provenance Sensitivity in LLM Agent Action Selection",
    "url": "https://arxiv.org/abs/2607.20827",
    "pdf_url": "https://arxiv.org/pdf/2607.20827",
    "published": "2026-07-22",
    "updated": "2026-07-22",
    "authors": [
      "Junchi Liao"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "memory",
      "tool-use"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent"
    ]
  },
  {
    "id": "2607.19947",
    "arxiv_id": "2607.19947",
    "source": "arxiv",
    "source_id": "arxiv:2607.19947",
    "title": "ETPDesigner: Multi-Agent Orchestration for Interactive Multimodal Electronic Theater Program",
    "url": "https://arxiv.org/abs/2607.19947",
    "pdf_url": "https://arxiv.org/pdf/2607.19947",
    "published": "2026-07-22",
    "updated": "2026-07-22",
    "authors": [
      "Mengtian Li",
      "Xinru Guo",
      "Xiaoru Lin",
      "Xiao Rong",
      "Zhifeng Xie",
      "Chaofeng Chen"
    ],
    "categories": [
      "cs.CV"
    ],
    "topics": [
      "agent-evaluation",
      "multi-agent"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.16900",
    "arxiv_id": "2607.16900",
    "source": "arxiv",
    "source_id": "arxiv:2607.16900",
    "title": "Environment-free Synthetic Data Generation for API-Calling Agents",
    "url": "https://arxiv.org/abs/2607.16900",
    "pdf_url": "https://arxiv.org/pdf/2607.16900",
    "published": "2026-07-21",
    "updated": "2026-07-21",
    "authors": [
      "Seanie Lee",
      "Sanjoy Chowdhury",
      "Chao Jiang",
      "Cheng-Yu Hsieh",
      "Ting-Yao Hu",
      "Alexander T Toshev",
      "Oncel Tuzel",
      "Raviteja Vemulapalli"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "memory",
      "rag",
      "tool-use",
      "workflow-agent",
      "world-model"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent"
    ]
  },
  {
    "id": "2607.19262",
    "arxiv_id": "2607.19262",
    "source": "arxiv",
    "source_id": "arxiv:2607.19262",
    "title": "BioSecBench-Surveillance: A Verifiable Benchmark for AI Agents in Pathogen Genomic Surveillance",
    "url": "https://arxiv.org/abs/2607.19262",
    "pdf_url": "https://arxiv.org/pdf/2607.19262",
    "published": "2026-07-21",
    "updated": "2026-07-21",
    "authors": [
      "Harmon Bhasin",
      "Kevin Flyangolts",
      "Dianzhuo Wang",
      "Evan Seeyave",
      "Arjun Banerjee",
      "Amanda Darling",
      "Joshua Stallings",
      "David Stern",
      "Shawn Higdon",
      "Claire Duvallet",
      "Bryan Tegomoh",
      "Kenny Workman"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "workflow-agent"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent"
    ]
  },
  {
    "id": "2607.19096",
    "arxiv_id": "2607.19096",
    "source": "arxiv",
    "source_id": "arxiv:2607.19096",
    "title": "Supra Cognitive Modes: A Routed Architecture for Agent Memory",
    "url": "https://arxiv.org/abs/2607.19096",
    "pdf_url": "https://arxiv.org/pdf/2607.19096",
    "published": "2026-07-21",
    "updated": "2026-07-21",
    "authors": [
      "Joshua Tobkin",
      "David Yang"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "memory",
      "rag",
      "reasoning"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "agent-memory",
    "matched_queries": [
      "agent-memory"
    ]
  },
  {
    "id": "2607.17951",
    "arxiv_id": "2607.17951",
    "source": "arxiv",
    "source_id": "arxiv:2607.17951",
    "title": "RT-SHCUA: Real-Time Self-Hosted Computer-Use Agent for UAV Control",
    "url": "https://arxiv.org/abs/2607.17951",
    "pdf_url": "https://arxiv.org/pdf/2607.17951",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Di Lu",
      "Bo Zhang",
      "Xiyuan Li",
      "Yongzhi Liao",
      "Xuewen Dong",
      "Yulong Shen",
      "Zhiquan Liu",
      "Jianfeng Ma"
    ],
    "categories": [
      "cs.CR"
    ],
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      "agent-evaluation",
      "agent-safety",
      "reasoning",
      "tool-use"
    ],
    "score": 14,
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    "primary_query": "language-agent",
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      "language-agent",
      "tool-use",
      "web-gui-agent"
    ]
  },
  {
    "id": "2607.17621",
    "arxiv_id": "2607.17621",
    "source": "arxiv",
    "source_id": "arxiv:2607.17621",
    "title": "Mechanistic Attention Guidance for Agent Memory Refinement",
    "url": "https://arxiv.org/abs/2607.17621",
    "pdf_url": "https://arxiv.org/pdf/2607.17621",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Yechao Hong",
      "Haiquan Qiu",
      "Yaqing Wang",
      "Quanming Yao"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "memory",
      "rag",
      "reasoning"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "agent-memory",
    "matched_queries": [
      "agent-memory"
    ]
  },
  {
    "id": "2607.18665",
    "arxiv_id": "2607.18665",
    "source": "arxiv",
    "source_id": "arxiv:2607.18665",
    "title": "SciHazard: A Benchmark for Measuring Scientific Safety Risks with Decomposed Harm Scoring",
    "url": "https://arxiv.org/abs/2607.18665",
    "pdf_url": "https://arxiv.org/pdf/2607.18665",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Chunxiao Li",
      "Yuan Xiong",
      "Lijun Li",
      "Tianyi Du",
      "Wenlong Zhang",
      "Lei Bai",
      "Jing Shao"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "computer-use",
      "rag",
      "tool-use"
    ],
    "score": 14,
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    "primary_query": "autonomous-agent-llm",
    "matched_queries": [
      "autonomous-agent-llm"
    ]
  },
  {
    "id": "2607.17879",
    "arxiv_id": "2607.17879",
    "source": "arxiv",
    "source_id": "arxiv:2607.17879",
    "title": "Exploratory and Assimilating Reflection: Reflective Recall Cycle for Long-term Memory",
    "url": "https://arxiv.org/abs/2607.17879",
    "pdf_url": "https://arxiv.org/pdf/2607.17879",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Ganesh Senrayan",
      "Moyuru Yamada",
      "Ishan Jindal",
      "Kiran Purohit"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "memory",
      "rag",
      "reasoning",
      "tool-use"
    ],
    "score": 14,
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    "primary_query": "autonomous-agent-llm",
    "matched_queries": [
      "autonomous-agent-llm"
    ]
  },
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    "id": "2607.13705",
    "arxiv_id": "2607.13705",
    "source": "arxiv",
    "source_id": "arxiv:2607.13705",
    "title": "AgentCompass: A Unified Evaluation Infrastructure for Agent Capabilities",
    "url": "https://arxiv.org/abs/2607.13705",
    "pdf_url": "https://arxiv.org/pdf/2607.13705",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Kai Chen",
      "Zichen Ding",
      "Jiaye Ge",
      "Shufan Jiang",
      "Mo Li",
      "Qingqiu Li",
      "Zehao Li",
      "Zonglin Li",
      "Tianhao Liang",
      "Shudong Liu",
      "Zerun Ma",
      "Zixin Shang",
      "Wenhui Tian",
      "Zun Wang",
      "Liwei Wu",
      "Zhenyu Wu",
      "Jun Xu",
      "Bowen Yang",
      "Dingbo Yuan",
      "Qi Zhang",
      "Songyang Zhang",
      "Peiheng Zhou",
      "Dongsheng Zhu"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "rag",
      "tool-use"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "autonomous-agent-llm",
    "matched_queries": [
      "autonomous-agent-llm"
    ]
  },
  {
    "id": "2607.16708",
    "arxiv_id": "2607.16708",
    "source": "arxiv",
    "source_id": "arxiv:2607.16708",
    "title": "Model-Driven Discipline for Multi-Agent LLMs: Requirement-to-Verification Generation of Traceable System Models",
    "url": "https://arxiv.org/abs/2607.16708",
    "pdf_url": "https://arxiv.org/pdf/2607.16708",
    "published": "2026-07-18",
    "updated": "2026-07-18",
    "authors": [
      "Ran Wei",
      "Le Zhu",
      "Haochi Wang",
      "Ruizhe Yang",
      "Jiapeng Guan",
      "Siyuan Ji",
      "Yuchen Hu",
      "Zhe Jiang",
      "Xiangyang Ji"
    ],
    "categories": [
      "cs.SE"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "multi-agent",
      "tool-use"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.16133",
    "arxiv_id": "2607.16133",
    "source": "arxiv",
    "source_id": "arxiv:2607.16133",
    "title": "When Do Multi-Agent Systems Help? An Information Bottleneck Perspective",
    "url": "https://arxiv.org/abs/2607.16133",
    "pdf_url": "https://arxiv.org/pdf/2607.16133",
    "published": "2026-07-17",
    "updated": "2026-07-17",
    "authors": [
      "Wendi Yu",
      "Lianhao Zhou",
      "Xiangjue Dong",
      "Sai Sudarshan Barath",
      "Declan Staunton",
      "Byung-Jun Yoon",
      "Xiaoning Qian",
      "James Caverlee",
      "Shuiwang Ji"
    ],
    "categories": [
      "cs.LG"
    ],
    "topics": [
      "agent-evaluation",
      "multi-agent",
      "reasoning"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.15193",
    "arxiv_id": "2607.15193",
    "source": "arxiv",
    "source_id": "arxiv:2607.15193",
    "title": "Plover: Steering GUI Agents through Plan-Centric Interaction",
    "url": "https://arxiv.org/abs/2607.15193",
    "pdf_url": "https://arxiv.org/pdf/2607.15193",
    "published": "2026-07-16",
    "updated": "2026-07-16",
    "authors": [
      "Madhumitha Venkatesan",
      "Shicheng Wen",
      "Jiajing Guo",
      "Jorge Piazentin Ono",
      "Liu Ren",
      "Dongyu Liu"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "planning",
      "tool-use",
      "workflow-agent"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "web-gui-agent",
    "matched_queries": [
      "web-gui-agent"
    ]
  },
  {
    "id": "2607.13618",
    "arxiv_id": "2607.13618",
    "source": "arxiv",
    "source_id": "arxiv:2607.13618",
    "title": "STOCKTAKE: Measuring the Gap Between Perception and Action in LLM Agents with a Fair Oracle",
    "url": "https://arxiv.org/abs/2607.13618",
    "pdf_url": "https://arxiv.org/pdf/2607.13618",
    "published": "2026-07-15",
    "updated": "2026-07-15",
    "authors": [
      "Sagar Deb",
      "Ashwanth Krishnan"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "tool-use"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "llm-agent",
    "matched_queries": [
      "llm-agent"
    ]
  },
  {
    "id": "2607.14386",
    "arxiv_id": "2607.14386",
    "source": "arxiv",
    "source_id": "arxiv:2607.14386",
    "title": "CIPHER: A Decoupled Exploration-Selection Framework for Test-Time Scaling of Data Science Agents",
    "url": "https://arxiv.org/abs/2607.14386",
    "pdf_url": "https://arxiv.org/pdf/2607.14386",
    "published": "2026-07-15",
    "updated": "2026-07-15",
    "authors": [
      "Maxime Heuillet",
      "Sharadind Peddiraju"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "rag",
      "tool-use",
      "workflow-agent"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent"
    ]
  },
  {
    "id": "2607.12122",
    "arxiv_id": "2607.12122",
    "source": "arxiv",
    "source_id": "arxiv:2607.12122",
    "title": "An Agentic AI Scientific Community for Automated Neural Operator Discovery",
    "url": "https://arxiv.org/abs/2607.12122",
    "pdf_url": "https://arxiv.org/pdf/2607.12122",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Luis Loo",
      "Ulisses Braga-Neto"
    ],
    "categories": [
      "cs.LG"
    ],
    "topics": [
      "agent-evaluation",
      "planning",
      "world-model"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "agentic-ai",
    "matched_queries": [
      "agentic-ai"
    ]
  },
  {
    "id": "2607.11444",
    "arxiv_id": "2607.11444",
    "source": "arxiv",
    "source_id": "arxiv:2607.11444",
    "title": "UMoE:Unlocking Every Expert in Domain-Specific Training",
    "url": "https://arxiv.org/abs/2607.11444",
    "pdf_url": "https://arxiv.org/pdf/2607.11444",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Xuefeng Li",
      "Pengfei Liu"
    ],
    "categories": [
      "cs.CL"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "rag",
      "tool-use"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "coding-agent",
    "matched_queries": [
      "coding-agent",
      "tool-use"
    ]
  },
  {
    "id": "2607.11126",
    "arxiv_id": "2607.11126",
    "source": "arxiv",
    "source_id": "arxiv:2607.11126",
    "title": "ToolAtlas: Learning Once, Reusing Everywhere with Tool-Side Memory",
    "url": "https://arxiv.org/abs/2607.11126",
    "pdf_url": "https://arxiv.org/pdf/2607.11126",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Yue Fang",
      "Zhibang Yang",
      "Fangkai Yang",
      "Xiaoting Qin",
      "Liqun Li",
      "Qingwei Lin",
      "Saravan Rajmohan",
      "Dongmei Zhang"
    ],
    "categories": [
      "cs.LG"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "memory",
      "tool-use"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "tool-use",
    "matched_queries": [
      "tool-use"
    ]
  },
  {
    "id": "2607.10265",
    "arxiv_id": "2607.10265",
    "source": "arxiv",
    "source_id": "arxiv:2607.10265",
    "title": "TGMS: An Agent-Native Bi-Temporal Graph Management System",
    "url": "https://arxiv.org/abs/2607.10265",
    "pdf_url": "https://arxiv.org/pdf/2607.10265",
    "published": "2026-07-11",
    "updated": "2026-07-11",
    "authors": [
      "Xiaofei Zhang"
    ],
    "categories": [
      "cs.DB"
    ],
    "topics": [
      "agent-evaluation",
      "planning",
      "rag",
      "reasoning",
      "tool-use"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "planning-agent",
    "matched_queries": [
      "planning-agent",
      "rag-agent"
    ]
  },
  {
    "id": "2607.10057",
    "arxiv_id": "2607.10057",
    "source": "arxiv",
    "source_id": "arxiv:2607.10057",
    "title": "Quantum Circuit Vision: Cost-Aware Evaluation of Visual AI Agents for Quantum Code Generation",
    "url": "https://arxiv.org/abs/2607.10057",
    "pdf_url": "https://arxiv.org/pdf/2607.10057",
    "published": "2026-07-10",
    "updated": "2026-07-10",
    "authors": [
      "Dongping Liu",
      "Aoyu Zhang",
      "Luyao Zhang"
    ],
    "categories": [
      "quant-ph"
    ],
    "topics": [
      "agent-evaluation",
      "reasoning"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent"
    ]
  },
  {
    "id": "2607.09996",
    "arxiv_id": "2607.09996",
    "source": "arxiv",
    "source_id": "arxiv:2607.09996",
    "title": "Who&When Pro: Can LLMs Really Attribute Failures in AI Agents?",
    "url": "https://arxiv.org/abs/2607.09996",
    "pdf_url": "https://arxiv.org/pdf/2607.09996",
    "published": "2026-07-10",
    "updated": "2026-07-10",
    "authors": [
      "Jiale Liu",
      "Huajun Xi",
      "Shaokun Zhang",
      "Yifan Zeng",
      "Tianwei Yue",
      "Chi Wang",
      "Jian Kang",
      "Qingyun Wu",
      "Huazheng Wang"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent"
    ]
  },
  {
    "id": "2607.09902",
    "arxiv_id": "2607.09902",
    "source": "arxiv",
    "source_id": "arxiv:2607.09902",
    "title": "Do These Violent Delights Have Violent Ends? Measuring the Post-Merge Fate of Agentic Code",
    "url": "https://arxiv.org/abs/2607.09902",
    "pdf_url": "https://arxiv.org/pdf/2607.09902",
    "published": "2026-07-10",
    "updated": "2026-07-10",
    "authors": [
      "Chunqiu Steven Xia",
      "Courtney Miller"
    ],
    "categories": [
      "cs.SE"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "coding-agent",
      "rag",
      "tool-use"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "coding-agent",
    "matched_queries": [
      "coding-agent"
    ]
  },
  {
    "id": "2607.09553",
    "arxiv_id": "2607.09553",
    "source": "arxiv",
    "source_id": "arxiv:2607.09553",
    "title": "Writing Bug Reports for Software Repair Agents: What Information Matters Most?",
    "url": "https://arxiv.org/abs/2607.09553",
    "pdf_url": "https://arxiv.org/pdf/2607.09553",
    "published": "2026-07-10",
    "updated": "2026-07-10",
    "authors": [
      "Vincenzo Luigi Bruno",
      "Alessandro Giagnorio",
      "Daniele Bifolco",
      "Leon Wienges",
      "Massimiliano Di Penta",
      "Gabriele Bavota"
    ],
    "categories": [
      "cs.SE"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "workflow-agent"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "coding-agent",
    "matched_queries": [
      "coding-agent"
    ]
  },
  {
    "id": "2607.08716",
    "arxiv_id": "2607.08716",
    "source": "arxiv",
    "source_id": "arxiv:2607.08716",
    "title": "Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents",
    "url": "https://arxiv.org/abs/2607.08716",
    "pdf_url": "https://arxiv.org/pdf/2607.08716",
    "published": "2026-07-09",
    "updated": "2026-07-09",
    "authors": [
      "Yifan Wu",
      "Lizhu Zhang",
      "Yuhang Zhou",
      "Mingyi Wang",
      "Bo Peng",
      "Serena Li",
      "Xiangjun Fan",
      "Zhuokai Zhao"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "memory",
      "planning",
      "rag",
      "tool-use"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "agent-memory",
    "matched_queries": [
      "agent-memory"
    ]
  },
  {
    "id": "2607.08983",
    "arxiv_id": "2607.08983",
    "source": "arxiv",
    "source_id": "arxiv:2607.08983",
    "title": "SCATE: Learning to Supervise Coding Agents for Cost-Effective Test Generation",
    "url": "https://arxiv.org/abs/2607.08983",
    "pdf_url": "https://arxiv.org/pdf/2607.08983",
    "published": "2026-07-09",
    "updated": "2026-07-09",
    "authors": [
      "Sijia Gu",
      "Noor Nashid",
      "Ali Mesbah"
    ],
    "categories": [
      "cs.SE"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "rag",
      "tool-use"
    ],
    "score": 14,
    "relevance": "high",
    "primary_query": "coding-agent",
    "matched_queries": [
      "coding-agent"
    ]
  },
  {
    "id": "2607.22031",
    "arxiv_id": "2607.22031",
    "source": "arxiv",
    "source_id": "arxiv:2607.22031",
    "title": "IDSTune: A Multi-Agent Collaborative Framework for Integrated Database System Tuning",
    "url": "https://arxiv.org/abs/2607.22031",
    "pdf_url": "https://arxiv.org/pdf/2607.22031",
    "published": "2026-07-24",
    "updated": "2026-07-24",
    "authors": [
      "Yiyan Li",
      "Guanli Liu",
      "Renata Borovica-Gajic",
      "Haoyang Li",
      "Zihang Qiu",
      "Xinmei Huang",
      "Andreas Kipf",
      "Cuiping Li",
      "Hong Chen"
    ],
    "categories": [
      "cs.DB"
    ],
    "topics": [
      "agent-evaluation",
      "multi-agent",
      "rag"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.21957",
    "arxiv_id": "2607.21957",
    "source": "arxiv",
    "source_id": "arxiv:2607.21957",
    "title": "KaPilot: LLM-Assisted Generation of Kani Specifications for Unsafe Rust Verification",
    "url": "https://arxiv.org/abs/2607.21957",
    "pdf_url": "https://arxiv.org/pdf/2607.21957",
    "published": "2026-07-24",
    "updated": "2026-07-24",
    "authors": [
      "Minghua Wang",
      "Yuxi Ling",
      "Mingzhi Gao",
      "Yuwei Liu",
      "Lin Huang"
    ],
    "categories": [
      "cs.SE"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "computer-use",
      "memory",
      "multi-agent",
      "tool-use"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.21824",
    "arxiv_id": "2607.21824",
    "source": "arxiv",
    "source_id": "arxiv:2607.21824",
    "title": "Protocol-Level Attacks on Agentic Commerce Platforms: A Cross-Platform Taxonomy, AIP-Bench, and Unified Defense",
    "url": "https://arxiv.org/abs/2607.21824",
    "pdf_url": "https://arxiv.org/pdf/2607.21824",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Yedidel Louck"
    ],
    "categories": [
      "cs.CR"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "tool-use"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent"
    ]
  },
  {
    "id": "2607.21495",
    "arxiv_id": "2607.21495",
    "source": "arxiv",
    "source_id": "arxiv:2607.21495",
    "title": "Toward Continuous Assurance for the Democratization of AI Agent Creation in Industry",
    "url": "https://arxiv.org/abs/2607.21495",
    "pdf_url": "https://arxiv.org/pdf/2607.21495",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Natan Levy",
      "Harel Berger"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "rag",
      "tool-use",
      "workflow-agent"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent"
    ]
  },
  {
    "id": "2607.20062",
    "arxiv_id": "2607.20062",
    "source": "arxiv",
    "source_id": "arxiv:2607.20062",
    "title": "Solar Open 2 Technical Report",
    "url": "https://arxiv.org/abs/2607.20062",
    "pdf_url": "https://arxiv.org/pdf/2607.20062",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Sungrae Park",
      "Sanghoon Kim",
      "Gyoungjin Gim",
      "Jungho Cho",
      "Hyunwoong Ko",
      "Minbyul Jeong",
      "Minjeong Kim",
      "Keunwoo Choi",
      "Chaehun Shin",
      "Chanwoong Yoon",
      "Dongjun Kim",
      "Eunwon Kim",
      "Gyungin Shin",
      "Hyeonju Lee",
      "Hyungkyu Kang",
      "Inseo Song",
      "Jisu Bae",
      "Jiyoon Han",
      "Jiyun Lee",
      "Joonkee Kim",
      "Junyeop Lee",
      "Mikyoung Cha",
      "Sangwon Yu",
      "Sehwan Joo",
      "Seokyoon Kang",
      "et al. (28 additional authors not shown)"
    ],
    "categories": [
      "cs.CL"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "planning",
      "rag",
      "tool-use",
      "workflow-agent"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "agent-evaluation",
    "matched_queries": [
      "agent-evaluation"
    ]
  },
  {
    "id": "2607.21268",
    "arxiv_id": "2607.21268",
    "source": "arxiv",
    "source_id": "arxiv:2607.21268",
    "title": "pAI-Econ-claude: A Gated Human-in-the-Loop Multi-Agent Architecture for AI-Assisted Economic Theory Development",
    "url": "https://arxiv.org/abs/2607.21268",
    "pdf_url": "https://arxiv.org/pdf/2607.21268",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Chen Zhu",
      "Xiaolu Wang",
      "Weilong Zhang"
    ],
    "categories": [
      "cs.MA"
    ],
    "topics": [
      "agent-evaluation",
      "multi-agent",
      "workflow-agent"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
  },
  {
    "id": "2607.03316",
    "arxiv_id": "2607.03316",
    "source": "arxiv",
    "source_id": "arxiv:2607.03316",
    "title": "Is Agentic Code Review Helpful? Mining Developers' Feedback to CodeRabbit Reviews in the Wild",
    "url": "https://arxiv.org/abs/2607.03316",
    "pdf_url": "https://arxiv.org/pdf/2607.03316",
    "published": "2026-07-23",
    "updated": "2026-07-23",
    "authors": [
      "Hong Yi Lin",
      "Mingzhao Liang",
      "Patanamon Thongtanunam",
      "Kla Tantithamthavorn"
    ],
    "categories": [
      "cs.SE"
    ],
    "topics": [
      "agent-safety",
      "coding-agent",
      "workflow-agent"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "autonomous-agent-llm",
    "matched_queries": [
      "autonomous-agent-llm"
    ]
  },
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    "id": "2607.19338",
    "arxiv_id": "2607.19338",
    "source": "arxiv",
    "source_id": "arxiv:2607.19338",
    "title": "CodeRescue: Budget-Calibrated Recovery Routing for Coding Agents",
    "url": "https://arxiv.org/abs/2607.19338",
    "pdf_url": "https://arxiv.org/pdf/2607.19338",
    "published": "2026-07-21",
    "updated": "2026-07-21",
    "authors": [
      "Qijia He",
      "Jiayi Cheng",
      "Chenqian Le",
      "Rui Wang",
      "Xunmei Liu",
      "Yixian Chen",
      "Jie Mei",
      "Zhihao Wang",
      "Xupeng Chen",
      "Yuhuan Chen",
      "Tao Wang"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "agent-safety",
      "coding-agent",
      "tool-use"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "coding-agent",
    "matched_queries": [
      "coding-agent"
    ]
  },
  {
    "id": "2607.18138",
    "arxiv_id": "2607.18138",
    "source": "arxiv",
    "source_id": "arxiv:2607.18138",
    "title": "AI Agent Communications in AI-Native 6G Network: Status, Challenges and Opportunities",
    "url": "https://arxiv.org/abs/2607.18138",
    "pdf_url": "https://arxiv.org/pdf/2607.18138",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Qiang Duan"
    ],
    "categories": [
      "cs.NI"
    ],
    "topics": [
      "multi-agent",
      "tool-use"
    ],
    "score": 13,
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    "primary_query": "agentic-ai",
    "matched_queries": [
      "agentic-ai",
      "ai-agent"
    ]
  },
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    "id": "2607.16057",
    "arxiv_id": "2607.16057",
    "source": "arxiv",
    "source_id": "arxiv:2607.16057",
    "title": "Frontier AI performance across the business disciplines: a case-grounded benchmark of knowledge work and analytical reasoning",
    "url": "https://arxiv.org/abs/2607.16057",
    "pdf_url": "https://arxiv.org/pdf/2607.16057",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Ajay Patel",
      "Kartik Hosanagar",
      "Ramayya Krishnan",
      "Chris Callison-Burch",
      "Karim Lakhani"
    ],
    "categories": [
      "cs.CL"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "reasoning",
      "tool-use"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "tool-use",
    "matched_queries": [
      "tool-use"
    ]
  },
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    "id": "2607.18171",
    "arxiv_id": "2607.18171",
    "source": "arxiv",
    "source_id": "arxiv:2607.18171",
    "title": "FlashRT: Agent Harness for Guiding Agents to Deploy Real-Time Multimodal Applications",
    "url": "https://arxiv.org/abs/2607.18171",
    "pdf_url": "https://arxiv.org/pdf/2607.18171",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Krish Agarwal",
      "Zhuoming Chen",
      "Yanyuan Qin",
      "Zhenyu Gu",
      "Atri Rudra",
      "Beidi Chen"
    ],
    "categories": [
      "cs.LG"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "computer-use",
      "world-model"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "coding-agent",
    "matched_queries": [
      "coding-agent"
    ]
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    "id": "2607.17527",
    "arxiv_id": "2607.17527",
    "source": "arxiv",
    "source_id": "arxiv:2607.17527",
    "title": "Sidekick: Designing Communication for Effective Multitasking with Computer Use Agents",
    "url": "https://arxiv.org/abs/2607.17527",
    "pdf_url": "https://arxiv.org/pdf/2607.17527",
    "published": "2026-07-20",
    "updated": "2026-07-20",
    "authors": [
      "Ruei-Che Chang",
      "Wenqian Xu",
      "Dingzeyu Li",
      "Bryan Wang",
      "Anhong Guo"
    ],
    "categories": [
      "cs.HC"
    ],
    "topics": [
      "computer-use",
      "multi-agent",
      "planning",
      "reasoning",
      "tool-use"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "web-gui-agent",
    "matched_queries": [
      "web-gui-agent"
    ]
  },
  {
    "id": "2607.17149",
    "arxiv_id": "2607.17149",
    "source": "arxiv",
    "source_id": "arxiv:2607.17149",
    "title": "A Diagnostic Framework for AI Agent Behavior",
    "url": "https://arxiv.org/abs/2607.17149",
    "pdf_url": "https://arxiv.org/pdf/2607.17149",
    "published": "2026-07-19",
    "updated": "2026-07-19",
    "authors": [
      "Xichen Zhang",
      "Yingjie Zhang",
      "Tianshu Sun"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "memory",
      "tool-use"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent"
    ]
  },
  {
    "id": "2607.15518",
    "arxiv_id": "2607.15518",
    "source": "arxiv",
    "source_id": "arxiv:2607.15518",
    "title": "A Tool-Invariant Framework for Teaching and Assessing Computational Methods in the Age of Agentic AI",
    "url": "https://arxiv.org/abs/2607.15518",
    "pdf_url": "https://arxiv.org/pdf/2607.15518",
    "published": "2026-07-16",
    "updated": "2026-07-16",
    "authors": [
      "Larry Engelhardt"
    ],
    "categories": [
      "physics.ed-ph"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "tool-use",
      "world-model"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "agentic-ai",
    "matched_queries": [
      "agentic-ai",
      "language-agent"
    ]
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  {
    "id": "2607.14548",
    "arxiv_id": "2607.14548",
    "source": "arxiv",
    "source_id": "arxiv:2607.14548",
    "title": "HyMobileAgent: Data-Environment Co-Scaling for Efficient GUI Agents",
    "url": "https://arxiv.org/abs/2607.14548",
    "pdf_url": "https://arxiv.org/pdf/2607.14548",
    "published": "2026-07-16",
    "updated": "2026-07-16",
    "authors": [
      "Hy Vision Team",
      "Huawen Shen",
      "Zhengyang Tang",
      "Shangpin Peng",
      "Liang Wu",
      "Anran Zhang",
      "Weinong Wang",
      "Yiduo Guo",
      "Chenxin Li",
      "Zhengyao Fang",
      "Yang Ding",
      "Junyi Li",
      "Fei Tang",
      "Zheng Ruan",
      "Yi Zhang",
      "Xingran Zhou",
      "Dingchen Yang",
      "Sunqi Fan",
      "Zhiyi Wan",
      "Han Hu",
      "Xin Lai",
      "Pengyuan Lyu",
      "Chengquan Zhang"
    ],
    "categories": [
      "cs.CV"
    ],
    "topics": [
      "computer-use",
      "embodied-agent",
      "planning",
      "reasoning",
      "tool-use"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "web-gui-agent",
    "matched_queries": [
      "web-gui-agent"
    ]
  },
  {
    "id": "2607.14456",
    "arxiv_id": "2607.14456",
    "source": "arxiv",
    "source_id": "arxiv:2607.14456",
    "title": "Beyond Generalist LLMs: Specialist Agentic Systems for Structured Code Workflow Execution",
    "url": "https://arxiv.org/abs/2607.14456",
    "pdf_url": "https://arxiv.org/pdf/2607.14456",
    "published": "2026-07-15",
    "updated": "2026-07-15",
    "authors": [
      "Harris Borman",
      "Herman Wandabwa",
      "Fusun Yu",
      "Sandeepa Kannangara",
      "Justin Liu",
      "Anna Leontjeva",
      "Ritchie Ng"
    ],
    "categories": [
      "cs.SE"
    ],
    "topics": [
      "tool-use",
      "workflow-agent"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "agentic-ai",
    "matched_queries": [
      "agentic-ai",
      "tool-use"
    ]
  },
  {
    "id": "2607.13027",
    "arxiv_id": "2607.13027",
    "source": "arxiv",
    "source_id": "arxiv:2607.13027",
    "title": "PalmClaw: A Native On-Device Agent Framework for Mobile Phones",
    "url": "https://arxiv.org/abs/2607.13027",
    "pdf_url": "https://arxiv.org/pdf/2607.13027",
    "published": "2026-07-14",
    "updated": "2026-07-14",
    "authors": [
      "Hongru Cai",
      "Yongqi Li",
      "Ran Wei",
      "Wenjie Li"
    ],
    "categories": [
      "cs.CL"
    ],
    "topics": [
      "computer-use",
      "memory",
      "tool-use",
      "workflow-agent"
    ],
    "score": 13,
    "relevance": "high",
    "primary_query": "tool-use",
    "matched_queries": [
      "tool-use"
    ]
  },
  {
    "id": "2607.12056",
    "arxiv_id": "2607.12056",
    "source": "arxiv",
    "source_id": "arxiv:2607.12056",
    "title": "Designing Agent-Ready Websites for AI Web Agents: A Framework for Machine Readability, Actionability, and Decision Reliability",
    "url": "https://arxiv.org/abs/2607.12056",
    "pdf_url": "https://arxiv.org/pdf/2607.12056",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Said Elnaffar",
      "Farzad Rashidi"
    ],
    "categories": [
      "cs.AI"
    ],
    "topics": [
      "agent-evaluation",
      "computer-use",
      "rag",
      "tool-use",
      "workflow-agent"
    ],
    "score": 13,
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    "primary_query": "ai-agent",
    "matched_queries": [
      "ai-agent",
      "web-gui-agent"
    ]
  },
  {
    "id": "2607.11423",
    "arxiv_id": "2607.11423",
    "source": "arxiv",
    "source_id": "arxiv:2607.11423",
    "title": "ToFu: A White-Box, Token-Efficient Agent Harness for Researchers",
    "url": "https://arxiv.org/abs/2607.11423",
    "pdf_url": "https://arxiv.org/pdf/2607.11423",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Junhao Ruan",
      "Yuan Ge",
      "Bei Li",
      "Yongjing Yin",
      "Yuchun Fan",
      "Xin Chen",
      "Jingang Wang",
      "Chenglong Wang",
      "Jingbo Zhu",
      "Tong Xiao"
    ],
    "categories": [
      "cs.CL"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "tool-use",
      "workflow-agent"
    ],
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    "relevance": "high",
    "primary_query": "tool-use",
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      "tool-use"
    ]
  },
  {
    "id": "2607.11565",
    "arxiv_id": "2607.11565",
    "source": "arxiv",
    "source_id": "arxiv:2607.11565",
    "title": "Heuristic Learning for Active Flow Control Using Coding Agents",
    "url": "https://arxiv.org/abs/2607.11565",
    "pdf_url": "https://arxiv.org/pdf/2607.11565",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Paul Garnier",
      "Jonathan Viquerat",
      "Elie Hachem"
    ],
    "categories": [
      "cs.LG"
    ],
    "topics": [
      "agent-evaluation",
      "coding-agent",
      "tool-use",
      "world-model"
    ],
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    "primary_query": "coding-agent",
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      "coding-agent"
    ]
  },
  {
    "id": "2607.11388",
    "arxiv_id": "2607.11388",
    "source": "arxiv",
    "source_id": "arxiv:2607.11388",
    "title": "StructAgent: Harness Long-horizon Digital Agents with Unified Causal Structure",
    "url": "https://arxiv.org/abs/2607.11388",
    "pdf_url": "https://arxiv.org/pdf/2607.11388",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Wenyi Wu",
      "Sibo Zhu",
      "Kun Zhou",
      "Aayush Salvi",
      "Zixuan Song",
      "Biwei Huang"
    ],
    "categories": [
      "cs.AI"
    ],
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      "computer-use",
      "planning",
      "reasoning",
      "tool-use",
      "workflow-agent"
    ],
    "score": 13,
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    "primary_query": "web-gui-agent",
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      "web-gui-agent"
    ]
  },
  {
    "id": "2607.11185",
    "arxiv_id": "2607.11185",
    "source": "arxiv",
    "source_id": "arxiv:2607.11185",
    "title": "SCALECUA: Scaling Computer Use Agents with Verifiable Task Synthesis and Efficient Online RL",
    "url": "https://arxiv.org/abs/2607.11185",
    "pdf_url": "https://arxiv.org/pdf/2607.11185",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Bowen Lv",
      "Xiao Liu",
      "Yanyu Ren",
      "Hanyu Lai",
      "Bohao Jing",
      "Hanchen Zhang",
      "Yanxiao Zhao",
      "Shuntian Yao",
      "Jie Tang",
      "Yuxiao Dong"
    ],
    "categories": [
      "cs.AI"
    ],
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      "computer-use",
      "multi-agent",
      "tool-use",
      "workflow-agent"
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    "primary_query": "web-gui-agent",
    "matched_queries": [
      "web-gui-agent"
    ]
  },
  {
    "id": "2607.11119",
    "arxiv_id": "2607.11119",
    "source": "arxiv",
    "source_id": "arxiv:2607.11119",
    "title": "VIA: Visual Interface Agent for Robot Control",
    "url": "https://arxiv.org/abs/2607.11119",
    "pdf_url": "https://arxiv.org/pdf/2607.11119",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Hengyuan Hu",
      "Priya Sundaresan",
      "Jensen Gao",
      "Dorsa Sadigh"
    ],
    "categories": [
      "cs.RO"
    ],
    "topics": [
      "coding-agent",
      "computer-use",
      "embodied-agent",
      "planning",
      "rag",
      "reasoning",
      "tool-use"
    ],
    "score": 13,
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    "primary_query": "web-gui-agent",
    "matched_queries": [
      "web-gui-agent"
    ]
  },
  {
    "id": "2607.12215",
    "arxiv_id": "2607.12215",
    "source": "arxiv",
    "source_id": "arxiv:2607.12215",
    "title": "Fine-Tuned Multi-Agent Framework for Detecting OCEAN in Life Narratives",
    "url": "https://arxiv.org/abs/2607.12215",
    "pdf_url": "https://arxiv.org/pdf/2607.12215",
    "published": "2026-07-13",
    "updated": "2026-07-13",
    "authors": [
      "Rasiq Hussain",
      "Darshil Italiya",
      "Joshua Oltmanns",
      "Mehak Gupta"
    ],
    "categories": [
      "cs.CL"
    ],
    "topics": [
      "agent-evaluation",
      "multi-agent",
      "reasoning"
    ],
    "score": 13,
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    "primary_query": "multi-agent-llm",
    "matched_queries": [
      "multi-agent-llm"
    ]
  }
]
