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

Paper: Mechanistic Attention Guidance for Agent Memory Refinement

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type: paper title: Mechanistic Attention Guidance for Agent Memory Refinement authors: Yechao Hong, Haiquan Qiu, Yaqing Wang, Quanming Yao year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.17621 code_url: source: arxiv collected_at: 2026-07-27 published_at: 2026-07-20 updated_at: 2026-07-20 status: queued relevance: high topics:

• agent-evaluation
• computer-use
• memory
• rag
• reasoning methods:

benchmarks:

models:

datasets:

• cs.AI related_concepts:

related_jobs:

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related_projects:

collection_score: 14 collection_queries: agent-memory

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: agent-memory
• inferred topics: agent-evaluation, computer-use, memory, rag, reasoning
• arXiv categories: cs.AI
• collection score: 14

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2607.17621