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agent/papers/items/2026-2606-29824-neural-procedural-memory-empowering-llm-agents-with-implicit-activation-steering.md
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Paper: Neural Procedural Memory: Empowering LLM Agents with Implicit Activation Steering


type: paper title: "Neural Procedural Memory: Empowering LLM Agents with Implicit Activation Steering" authors: Chengfeng Zhao, Yuqiao Tan, Shizhu He, Yequan Wang, Jun Zhao, Kang Liu year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.29824 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-29 updated_at: 2026-06-29 status: queued relevance: high topics:

  • agent-evaluation
  • computer-use
  • memory
  • rag
  • tool-use
  • workflow-agent methods:

benchmarks:

models:

datasets:

  • cs.CL
  • cs.AI related_concepts:

collection_score: 24 collection_queries: agent-evaluation, agent-memory, autonomous-agent-llm, llm-agent, rag-agent

One-line Takeaway

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

Why Collected

  • matched queries: agent-evaluation, agent-memory, autonomous-agent-llm, llm-agent, rag-agent
  • inferred topics: agent-evaluation, computer-use, memory, rag, tool-use, workflow-agent
  • arXiv categories: cs.CL, cs.AI
  • collection score: 24

Review Checklist

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