Pai 的 AI 雷达

今日必看

含近几日仍热话题，按时间衰减排序。今天先看 alirezarezvani/claude-skills，其次 Agent Atoll: Visualise your Claude Code/Codex history on a 3D living archipelago。并行还有 Battle Drones–a vibe coded RTS with audio-based multiplayer、Claude Code Spotted a Cryptominer on Mac While Building a Temperature App。

日期
2026/10/21
今日条目
110
往期2026/10/21
全部110编码代理21Agent与工具6个人助理6模型与评测29创作成片11开发与开源18产品接入19
领域机器人具身10硬件边缘2生信医疗2金融2教育1安全治理4行业观察8创业者1

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#51

AM-Bench: A Unified Taxonomy and Evaluation Suite for Agentic Misalignment

arXiv:2610.24264v2 Announce Type: replace Abstract: As LLM-based agents are deployed with increasing autonomy in real-world environments, a critical failure mode emerges: agentic misalignment, where agents choose harmful actions over failure. However, existing safety benchmarks p

推荐理由AM-Bench: A Unified Taxonomy：arXiv:2610.24264v2 Announce Type: replace Abstract: As LLM-based agents are deployed。
模型与评测安全治理arXiv cs.AI 官方
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#52

Aptamers as a sandbox for lab-in-the-loop agentic molecular discovery

arXiv:2610.24806v1 Announce Type: cross Abstract: Despite breakthroughs in AI-driven molecular generation, existing discovery pipelines operate largely in silico, with wet-lab feedback reserved for validation rather than iterative improvement. Whether large language model (LLM)-b

推荐理由Aptamers as a sandbox：arXiv:2610.24806v1 Announce Type: cross Abstract: Despite breakthroughs in AI-driven。
模型与评测arXiv cs.AI 官方
arxiv.org打开原文
#53

ClawMMU: Protection-Coherent Virtual Memory for Stateful LLM Agents

arXiv:2610.28093v1 Announce Type: cross Abstract: AI agents keep long-term memory, much of which comes from web pages and tool results. Agent harnesses, the software that runs the model, do not record who may act on this memory, so an instruction hidden in a fetched page can be t

推荐理由ClawMMU: Protection-Coherent Virtual：arXiv:2610.28093v1 Announce Type: cross Abstract: AI agents keep long-term memory, much。
模型与评测arXiv cs.AI 官方
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#54

Does Multi-Agent Collaboration Reduce Hallucination in Clinical Tasks?

arXiv:2610.27027v1 Announce Type: new Abstract: Multi-agent LLM systems improve performance on clinical tasks, and that improvement is often read as evidence of a more trustworthy system. However, the two are not the same claim. A clinician acts on the stated reasoning and not on

推荐理由Does Multi-Agent Collaboration Reduce：arXiv:2610.27027v1 Announce Type: new Abstract: Multi-agent LLM systems improve。
模型与评测生信医疗arXiv cs.AI 官方
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#56

Industrial Agentic AI: LLM-Driven New-Generation Agents for Smart Manufacturing

arXiv:2610.26941v1 Announce Type: new Abstract: Large language models (LLMs) are enabling agents to move beyond predefined workflows toward autonomous planning and execution, creating new opportunities for smart manufacturing. However, dynamic environments, complex physical const

推荐理由Industrial Agentic AI: LLM-Driven：arXiv:2610.26941v1 Announce Type: new Abstract: Large language models (LLMs) are。
模型与评测arXiv cs.AI 官方
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#57

Local Work, Global Progress: A Convergence Theory of AI Agent Collaboration

arXiv:2610.28286v1 Announce Type: cross Abstract: Teams of large language model (LLM) agents are increasingly applied to complex tasks, but their collaboration protocols are mostly designed empirically, without convergence guarantees. We formalize collaborative problem solving as

推荐理由Local Work, Global Progress:：arXiv:2610.28286v1 Announce Type: cross Abstract: Teams of large language model (LLM)。
模型与评测arXiv cs.AI 官方
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#58

MAS-Guard: Unified Guardrails from Individual Agents to Multi-Agent LLM Systems

arXiv:2610.28397v1 Announce Type: cross Abstract: Agentic AI extends large language models (LLMs) from generating responses to planning and executing complex workflows, substantially expanding their utility while exposing applications to unsafe actions, information leakage, and a

推荐理由MAS-Guard: Unified Guardrails from：arXiv:2610.28397v1 Announce Type: cross Abstract: Agentic AI extends large language。
模型与评测安全治理arXiv cs.AI 官方
arxiv.org打开原文