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Semantic Uncertainty-Guided Orchestration in Hierarchical Multi-Agent Systems
从语义不确定性切入，为层级多智能体协作提供全新编排思路，适合关注大模型Agent与系统优化的读者。
arXiv:2608.14707v1 Announce Type: new Abstract: As large language model (LLM)-based multi-agent systems become increasingly capable, coordinating agen…
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AI Workflow Orchestration: How AI Agents Can Work Like Your Engineering Team
AI智能体如何像工程团队一样协同工作？从导师Agent出发，重构你的AI开发工作流
Imagine you are a beginner developer. You have been asked to build a new feature: “Add authentication to the application.” You open your AI coding age…
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Show HN: Kota – Bring AI agent CLIs into the same room
让多个AI agent命令行齐聚一堂，实时协作管理智能体会话，堪称智能体调度中枢。
A couple months ago, I was tired of keep copy-paste across different Agent Chatbot tabs, feeling like a slave for AI sessions, so I created Kota for m…
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中国工程院外籍院士赫尔佐格：AI 下一个突破口是小型智能体协作
德国院士预言：AI未来不在巨型模型，而在于小智能体协同作战。
IT之家 7 月 26 日消息，据央视新闻今日报道，德国国家工程科学院院士、中国工程院外籍院士赫尔佐格荣获 2025 年度中华人民共和国国际科学技术合作奖。近日，赫尔佐格接受总台《高端访谈》栏目专访时谈到人工智能发展，他表示， 人工智能领域下一次重大突破绝非单一大型系统，而是众多小型的专业化智能体协…
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Show HN: OtoDock, run Claude Code and Codex as a team of agents on your server
自托管Claude Code/Codex，让多个AI智能体协作执行任务，支持定时触发与严重级别警报。
Hi HN, i am Dimitris, I have been using Claude Code and Codex agents, for some time now from the beggining i had been using them from inside my termin…
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Meta 发布多模态推理模型 Muse Spark 1.1，强化 AI 智能体任务能力
Meta新模型Muse Spark 1.1主打多智能体协作与百万级上下文，让AI能拆解任务并行执行，效率倍增。
IT之家 7 月 12 日消息，Meta 于 7 月 9 日正式发布适用于 AI 智能体的多模态推理模型 Muse Spark 1.1 版本，重点提升了模型在智能体任务中的规划、协同与执行能力，并增强了工具调用、代码开发、应用操作能力。 Meta 表示，Muse Spark 1.1 强化了多智能体协…
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Show HN: Agent Bus – IRC-style message bus for AI agents (MCP)
IRC式消息总线，让AI智能体像进群聊天一样协作，基于MCP协议，开源即用。
Article URL: https://github.com/roriau0422/AgentBus Comments URL: https://news.ycombinator.com/item?id=48823632 Points: 1 # Comments: 0
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Build an agent first Kanban board
开源看板anban，专为多AI agent设计，实现任务协同与可视化追踪。
Hi, I have been building an open source kanban board that serves as a way for my multiple Hermes and OpenClaw agents to communication with each other …
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ReM-MoA: Reasoning Memory Sustains Mixture-of-Agents Scaling
提出ReM-MoA机制，用推理记忆解决混合代理规模化难题，提升多智能体协作效率。
arXiv:2606.24437v1 Announce Type: new Abstract: Mixture-of-Agents (MoA) architectures improve inference-time scaling by organizing multiple LLM agents…
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CoCoSI: Collaborative Cognitive Map Construction for Spatial Intelligence
新框架CoCoSI让多个智能体协作构建认知地图，突破空间智能瓶颈
arXiv:2606.10401v1 Announce Type: new Abstract: Spatial intelligence is a key frontier for multimodal large language models (MLLMs), enabling them to …
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DIG to Heal: Scaling General-purpose Agent Collaboration via Explainable Dynamic Decision Paths
通用智能体协作新框架，用可解释动态决策路径破解规模化合作难题
arXiv:2603.00309v2 Announce Type: replace Abstract: The increasingly popular agentic AI paradigm promises to harness the power of multiple, general-pu…
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When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems
LLM多智能体系统执行无误却规划失效？这篇论文提出“认知校准”新方法，破解隐藏的推理偏差。
arXiv:2605.23414v1 Announce Type: new Abstract: LLM-based multi-agent systems can fail even when planned actions are executed correctly because agents…
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Polis – a Markdown protocol for AI agent teams that get better over time
用Markdown文件驱动多模型AI代理协作，实现任务路由与自我优化，让团队越用越强
Article URL: https://github.com/yehudalevy-collab/polis-protocol Comments URL: https://news.ycombinator.com/item?id=48171752 Points: 2 # Comments: 0