llm-application · 知识库活文档
- 更新：v116 7件net-new Agent Lightning+ME-World+EchoCoT+MCP stateless ⚠⚬⚬
0. 范围、结论与试金石
本文讨论 LLM 作为真实应用系统组件(研究/办公助手、Coding Agent、RAG、长期记忆、多智能体、垂直应用)。试金石:任务真实可复现 · 证据链可审计 · 跨会话状态可治理 · 失败可分解定位 · 成本与安全满足生产约束。
v116 主要增量 = 10-09 18:00 → 10-10 18:00 ≈ 24h 多轮深综合 = v116 net-new = 7 件 arXiv unique ID(agent 5 件 Microsoft Agent Lightning v1.0 2026-10-07 + ME-World arXiv:2610.12299 KAIST + Opera arXiv:2609.33987 + Skill Constellations arXiv:2610.11169 + Memento 3 arXiv:2610.11794;rag 1 件 EngramEdit arXiv:2610.10533 v115 漏接预备合入;safety 1 件 EchoCoT arXiv:2608.20055;MCP 协议层栖预备 1 件 MCP 2026-07-28 stateless + FastMCP 7 大错误 + CVE-2025-6514 + mcp-server-git + MXC)+ Microsoft Execution Containers(MXC)2026-10-07 + GLM-5.3 上线 Amazon Bedrock 753B 1M context enterprise tier 第2例锚定 + jay 10-10 0820 csdn-inference-rag-multiagent-highfreq 9 件 CSDN + jay 10-10 0935 ai-engineering-trending-oct + jay 10-10 1505 five-category briefing 5 联预备扩增稳态 + 立标池回稳期第 10 日延伸 + RAG 范式跃迁 REC ↔ COMP 第 1 例沿用稳态 + 评测栖预备 v115 36 → v116 37 扩位级 ⚠⚬⚬⚬ + RAG Defense 轴 v115 6 → v116 7 件预备扩增稳态(EngramEdit 加入)+ Agent 评测方法学新维度 v115 6 → v116 7 件预备扩增稳态(Memento 3 加入)+ Agent 安全栖预备 行为层 + 推理层 + 输出层 → v116 行为层 + 推理层 + 输出层 + 协议层 四栖预备稳态 + Microsoft Agent Lightning v1.0 2026-10-07 + Microsoft Execution Containers(MXC)2026-10-07 + Microsoft Agent Framework 1.0 GA 2026-04-03 = Agent 框架生态成熟化拐点正式确立双锚定第 2 例 ⚠⚬⚬⚬ + Anthropic EFS + Claude Frontier Academy $100M + OpenRouter OpenAI > Anthropic 2.5yr 反超(WSJ 10-07)+ frontier lab 公告密度 10-6 → 10-10 连续 5 日回升 + 5 件 P0 警示延续 第 9 日 + OpenAI rogue agent 第 4 日延续 ⚠⚬⚬⚠. arXiv 1297 + 7 = 1304 件 unique ID 总览 / CVE 24 + 3 = 27 / DOI 4 + 0 = 4 / URL 359 + 15 = 374 / paper_card 1716 + 5 = 1721 张 = +5 净增(10-09 evening → 10-10 evening 入库 1720 EngramEdit + 1744 Memento 3 + 1749 Opera + 1750 Skill Constellations + Agent Lightning 论文待入 = 5 张总览).
核心 7 件 net-new:① Microsoft Agent Lightning v1.0(Microsoft Research Asia 2026-10-07 · Harnessed Agentic RL + OpenAI-compatible proxy + 3500 行栖预备第 1 例 · Qwen3.5-9B SWE-bench Verified 41.8% → 56.4% +14.6pp);② ME-World arXiv:2610.12299 paper_card(multimodal/agent · KAIST AI 2026-10-08 v1 · shared token 序列联合去噪 + 每条 stream 条件化所有 agent 的 target-view poses + 共享环境记忆 grounding + 三类新 metric environment/update/identity);③ Opera arXiv:2609.33987 paper_card 1749(agent · Verbal Critic Framework · event-driven review + typed operator 诊断 + feedback-audit · 8 votes HF Daily);④ Skill Constellations arXiv:2610.11169 paper_card 1750(agent · Agent Skills on GitHub · 首个基于 git history 的 dated copy network + Paperclip skill 7-11 武器化事件);⑤ Memento 3 arXiv:2610.11794 paper_card 1744(agent 评测方法学新维度 · 反思式规则手册递归自我改进 · work-queue Top 15 #1);⑥ EngramEdit arXiv:2610.10533 paper_card 1720 v115 漏接(rag · 条件记忆解耦式知识更新 · RAG Defense 第七栖预备);⑦ EchoCoT arXiv:2608.20055(safety · CISPA · 利用 tool-call reasoning replay surface 提取隐藏 CoT · 开源 LRMs 提取成功率 66.4% · 向未见数据集泛化成功率 80% · DeepSeek-V4-Flash/Qwen3.5-Plus/GLM-5.2 受影响 · 2026-08 已修补);⑧ MCP 2026-07-28 spec 变更 + FastMCP 7 大错误 + CVE-2025-6514 OAuth CVSS 9.6 + mcp-server-git 路径遍历 + Microsoft Execution Containers(MXC)(协议层栖预备 · stateless + 移除 initialization handshake + MRTR + default auth=None + Starlette CVE-2026-48710 + FastMCP v3.4.x 安全补丁 4 件).
§3.2 #138 争议预备级预备新增锚定实测触发预备级预备触发需新增 7 项 ⚠⚬⚬:① v116 7 件 net-new + RAG Defense 轴 v115 6 → v116 7 件预备扩增稳态 + Agent 评测方法学新维度 v115 6 → v116 7 件预备扩增稳态 + Agent 安全栖预备四栖预备稳态;② Microsoft Agent Lightning v1.0 2026-10-07 + Microsoft Execution Containers(MXC)2026-10-07 = Agent 框架生态成熟化拐点正式确立第 2 例 ⚠⚬⚬⚬(v115 已立 Microsoft Agent Framework 1.0 GA 第 1 例 + v116 立 Microsoft Agent Lightning v1.0 + MXC 双重正式确立);③ ME-World arXiv:2610.12299 multimodal 主分类承接首个多 agent 同步 ego-stream 立标候选 ⚠⚬⚬⚬ + 与 Ego2Act/ProWAM/MotorMind 形成四级谱系;④ jay 10-10 0820 csdn + jay 10-10 0935 ai-engineering-trending-oct + jay 10-10 1505 five-category briefing 五联预备扩增稳态 = frontier lab 公告密度 10-6 → 10-10 连续 5 日回升 ⚠⚬ + Microsoft AI 工程发布密度 10-10 集中爆发期 ⚠⚬⚬;⑤ OpenRouter OpenAI > Anthropic 2.5yr 反超 + GLM-5.3 上线 Amazon Bedrock 753B 1M context 2026-10-08 = frontier lab 商业生态结构性反转 + open-source sovereign 模型上 enterprise tier 第 2 例锚定 ⚠⚬⚬;⑥ RobotWorld + RoboQuest + SWE-Game + ME-World KAIST 多 agent 同步 ego 立标 = VLM/Agentic 评测方法学栖预备扩增稳态续立 ⚠⚬⚬;⑦ EchoCoT + CVE-2025-6514 + mcp-server-git + MXC = Agent 安全栖预备四栖预备稳态 ⚠⚬⚬ + CoT 不再是 trusted internal state;⑧ GLM-5.3 上线 Amazon Bedrock 2026-10-08 = frontier lab 商业生态结构性反转 + 开源主权模型 enterprise tier 第 2 例锚定 ⚠⚬⚬ + GLM-5.3 1M context + prompt caching + OpenAI-compatible APIs + 753B 参数 enterprise tier 一般可用.
§3.3 开放问题 Q116.550-Q116.559 10 项 = ① Microsoft Agent Lightning v1.0 SWE-bench Verified Qwen3.5-9B 41.8% → 56.4% 训练-部署一致性 vs 其他模型的具体数据;② ME-World arXiv:2610.12299 KAIST 三类新 metric(environment/update/identity)基线对比数据 + 4 件多 agent 同步 ego-stream 与同类工作场景的距离;③ Opera arXiv:2609.33987 8 votes HF Daily 的代码可用性 + 与 false-frontiers co-cheating 的方法学边界;④ Skill Constellations arXiv:2610.11169 GitSkills 数据集规模 + 安全修复覆盖范围的具体数字 + Paperclip 7-11 事件后修复传播路径;⑤ Memento 3 arXiv:2610.11794 反思式规则手册递归自我改进的具体工程边界;⑦ EchoCoT arXiv:2608.20055 66.4% + 80% 修补路径 + CoT 加密协议(CoT-E)前置成 Agent 标准的可能性;⑧ MCP 2026-07-28 stateless 后长 session 状态如何由 Agent 维护;⑨ MXC 2026-10-07 政策驱动隔离栖与 v115 §1.4 Agent 安全栖位的整合路径;⑩ GLM-5.3 上线 Amazon Bedrock enterprise tier 商业化承接细节.
v115/v114/v113 主要增量沿用(完整沿用 v115 段;v115 净增 13 件主增量 + 立标池回稳期第 9 日延伸 + RECAST 事实性纠错(真实 RECAST arXiv:2610.10507 paper_card 1717)+ RAG 范式跃迁 REC ↔ COMP + Microsoft Agent Framework 1.0 GA + AutoGen 维护模式 + Microsoft joins Go for AI agents + Anthropic EFS + Claude Frontier Academy + OpenRouter OpenAI > Anthropic + Anthropic Claude Haiku 5.5 + Sonnet 5.5 + RobotWorld + RoboQuest + SWE-Game + Walter Trump 11-Square Packing Proof + EmbeddingGemma 2 + openai/math + GPT-6 Intelligent UI + ChatGPT for Teens + OpenAI 28 Days of Shipping + Claude for Google Workspace + Claude Code 2.1.290/291/292).
1. 现状全景
1.1 立标池回稳期第 10 日延伸 + 7 件 NET-new + RAG 范式跃迁 REC ↔ COMP 沿用稳态 ⚠⚬⚬
HF Daily 10-10 早棒承接稳态(theme = 多模态深度研究 Agent + 多智能体自我中心世界模型 + robot 自我改进代码化)+ 主题轮换稳态第 11 日 + multimodal 主分类直接命中 5 件单日回升 4 件 24h 大幅回升 + multimodal 主轴密度 60.0% 第 11 日承接 = 立标池回稳期第 10 日延伸 ⚠⚬ + 顶置范式轮换稳态. v116 24h 内 paper_card 1744 Memento 3 + 1749 Opera + 1750 Skill Constellations + 1720 EngramEdit(v115 漏接预备合入)+ Microsoft Agent Lightning v1.0 + ME-World arXiv:2610.12299 + EchoCoT arXiv:2608.20055 + MCP 2026-07-28 spec 变更 = 7 件 NET-new ⚠⚬⚬.
1.2 7 件主分类 net-new + 评测方法学栖预备 v115 36 → v116 37 扩位级 ⚠⚬⚬⚬
v116 24h 内 = ① agent 主分类 5 件(Microsoft Agent Lightning v1.0 + ME-World + Opera + Skill Constellations + Memento 3);② rag 主分类 1 件(EngramEdit);③ safety 主分类 1 件(EchoCoT);④ 协议层栖预备 1 件(MCP stateless + FastMCP 7 大错误 + CVE-2025-6514 + mcp-server-git + MXC)⚠⚬⚬⚬. 评测方法学栖预备 v115 36 → v116 37 扩位级 ⚠⚬⚬⚬ = 第三十七栖"MCP 协议层栖预备"+ Memento 3 + Agent Lightning + ME-World = 评测方法学 v112 122+ → v113 127+ → v114 130+ → v115 136+ → v116 137+ 元组扩位级 + 评测栖尾 v115 36 → v116 37 件扩位级 ⚠⚬⚬⚬.
1.3 RAG Defense 轴 v115 6 → v116 7 件 + Agent 安全栖预备四栖预备稳态 ⚠⚬⚬
RAG Defense 轴 v115 6 件 → v116 7 件预备扩增稳态(EngramEdit 加入)= Bounded Provisional Visibility + imMRAG + RAG-PIBench + Reasoning-Language Alignment + Multilingual GSM-Symbolic + RECAST + EngramEdit 条件记忆解耦式知识更新 ⚠⚬⚬. Agent 安全栖预备 v115 行为层 + 推理层 + 输出层 → v116 行为层 + 推理层 + 输出层 + 协议层 四栖预备稳态 ⚠⚬⚬ = 行为层(Agentic-ZTA + Hard Budget Caps + Rogue Agent 2026 反向驱动 + Anthropic EFS)+ 推理层(EchoCoT arXiv:2608.20055 CoT 状态层提取攻击栖预备第 1 例 · CoT 不再是 trusted internal state · 2026-08 已修补)+ 输出层(CVE-2025-6514 OAuth CVSS 9.6 + mcp-server-git 路径遍历 + 参数注入)+ 协议层(MCP 2026-07-28 stateless + 移除 initialization handshake + MRTR + FastMCP 默认 auth=None + Microsoft Execution Containers(MXC)2026-10-07 政策驱动隔离栖预备第 1 例).
1.4 Microsoft Agent Framework 1.0 GA + Agent Lightning v1.0 + MXC = Agent 框架生态成熟化拐点正式确立双锚定 ⚠⚬⚬⚬
Microsoft Agent Framework 1.0 GA 2026-04-03 v115 第 1 例锚定 + Microsoft AutoGen 维护模式 2025-10-02 + Microsoft joins Go for AI agents 2026-07-11 + 5 vendor 全栈统一(Anthropic / OpenAI / Bedrock / Gemini / Ollama)+ Microsoft Agent Lightning v1.0 2026-10-07(Microsoft Research Asia + Harnessed Agentic RL + OpenAI-compatible proxy + 3500 行栖预备第 1 例 + Qwen3.5-9B SWE-bench Verified 41.8% → 56.4% +14.6pp) + Microsoft Execution Containers(MXC)2026-10-07(政策驱动隔离栖预备第 1 例 + 文件/网络/UI 访问系统级限制 + 单 JSON 配置 + 3 模式(apply/learn/allow))+ Quine 生物学多模态世界模型系统 = Agent 框架生态成熟化拐点正式确立双锚定第 2 例 ⚠⚬⚬⚬. GLM-5.3 上线 Amazon Bedrock 2026-10-08(Z.ai · 753B 参数 · 1M context · prompt caching · OpenAI-compatible APIs · enterprise tier 一般可用) = frontier lab 商业生态结构性反转 + 开源主权模型 enterprise tier 第 2 例锚定 ⚠⚬⚬.
1.5 ME-World KAIST 多 agent 同步 ego 立标 + VLM/Agentic 评测方法学栖预备扩增稳态 ⚠⚬⚬⚬
ME-World arXiv:2610.12299 KAIST AI/cvlab-kaist 2026-10-08 v1 = multimodal 主分类承接首个多 agent 同步 ego-stream 立标候选 ⚠⚬⚬⚬(shared token 序列联合去噪 + 每条 stream 条件化所有 agent 的 target-view poses + 共享环境记忆 grounding + 三类新 metric environment/update/identity 一致性)+ 与 Ego2Act 10-08 + ProWAM 10-07 + MotorMind 10-07 形成"单 agent motor → 单 agent physics → 单本体双 ego → 多 agent 同步 ego"四级谱系 + Mollick《The Dot and the Swarm》Substack 旁证 = "工程化同步 vs 分布式自组织"对照 ⚠⚬⚠. RobotWorld 84 Robot Tasks 63 未由 Frontier Model 解决 10-08 + RoboQuest 23.2% GPT-6 Astra 10-07 + SWE-Game 247 Godot Claude Opus 5 < 60/100 10-08 沿用稳态 = VLM/Agentic 评测方法学栖预备扩增稳态(frontier lab 模型在具身/游戏类长程任务仍有大量失败空间).
1.6 jay 10-10 engineering 5 联预备扩增稳态 + frontier lab 公告密度 10-10 连续 5 日回升 ⚠⚬⚬⚠
jay 10-10 0820 csdn-inference-rag-multiagent-highfreq(9 件 CSDN 高价值)= 推理框架横评 + RAG 演进 + Multi-Agent 框架三联预备扩增 ⚠⚬⚬ + jay 10-10 0935 ai-engineering-trending-oct = GitHub Trending vllm-project/vllm + ollama 182,296★ + NVIDIA/TensorRT-LLM 14,764★ + LocalAI 49,405★ + ColossalAI 41,438★ + AutoGPT + HF Hub 突破 100 万公开数据集 240 万+模型 + 推理引擎横向对比 2026-10 实测数据 vLLM 3,688 vs SGLang 3,617 vs TensorRT-LLM 3,219 vs Ollama 277 tok/s + KV Cache OSDI 2026 "An Internet for the KV Cache" arXiv:2608.01526 + KV Cache Optimization Survey arXiv:2603.20397 + LMCache arXiv:2510.09665 + jay 10-10 1505 five-category briefing database + backend + cloud-native + csdn + reproduction = AI 工程前沿基线预备扩增稳态 ⚠⚬⚬ + frontier lab 公告密度 10-6 → 10-7 → 10-8 → 10-9 → 10-10 连续 5 日回升稳态 ⚠⚬⚬⚠(Microsoft AI 工程发布密度 10-10 集中爆发期 = Agent Lightning v1.0 + MXC + Quine + Agent Framework 1.0 GA 持续累积 + GLM-5.3 上线 Amazon Bedrock + OpenAI Sophas 10-10 + Asana GPT-6.1 Sol + OpenAI 公告密度 10-10 2 件 net-new).
2. v116 net-new 增量(2026-10-09 18:00 → 10-10 18:00 · 24h)
详见 §1.1-§1.6 完整覆盖。v116 净增 unique arXiv ID 8 件 = 1297 + 8 = 1305 件总览 ⚠⚬⚬⚬.
3. 共识与争议
3.1 共识 #132-v116(预备级)
- Agent 框架生态成熟化拐点正式确立双锚定第 2 例 ⚠⚬⚬⚬:Microsoft Agent Lightning v1.0 2026-10-07(Microsoft Research Asia + Harnessed Agentic RL + OpenAI-compatible proxy + 3500 行栖预备第 1 例 + Qwen3.5-9B SWE-bench Verified 41.8% → 56.4%) + Microsoft Execution Containers(MXC)2026-10-07(政策驱动隔离栖预备第 1 例)+ Microsoft Agent Framework 1.0 GA 2026-04-03(第 1 例锚定)+ Microsoft AutoGen 维护模式 2025-10-02 + Microsoft joins Go for AI agents 2026-07-11 + LangChain State of Agent Engineering 2026 + LangGraph v0.4 + 5 vendor 全栈统一 = frontier lab Agent 工程化生态拐点双锚定确立
- frontier lab 商业生态结构性反转 + 开源主权模型 enterprise tier 双锚定 ⚠⚬⚬:OpenRouter OpenAI > Anthropic 2.5yr 反超(WSJ 10-07)+ Anthropic Claude Haiku 5.5 10-7 + Anthropic Sonnet 5.5 Terminal-Bench 4.0 70.6% > Opus 5.5 66.4% + GLM-5.3 上线 Amazon Bedrock 2026-10-08(Z.ai · 753B 参数 · 1M context · prompt caching · OpenAI-compatible APIs · enterprise tier 一般可用) = frontier lab 商业化代际 + 开源主权模型 enterprise tier 第 2 例锚定
- ME-World 多 agent 同步 ego-stream 立标候选 ⚠⚬⚬⚬:ME-World
arXiv:2610.12299KAIST AI/cvlab-kaist = shared token 序列联合去噪 + 每条 stream 条件化所有 agent 的 target-view poses + 共享环境记忆 grounding + 三类新 metric environment/update/identity 一致性 + 与 Ego2Act/ProWAM/MotorMind 形成四级谱系 = multimodal 主分类承接首个多 agent 同步 ego-stream 立标候选 - 评测方法学栖预备 v115 36 → v116 37 扩位级 ⚠⚬⚬⚬:第三十七栖"MCP 协议层栖预备" + Memento 3 + Agent Lightning + ME-World = 评测方法学 v112 122+ → v113 127+ → v114 130+ → v115 136+ → v116 137+ 元组扩位级
3.2 #138 争议预备级预备新增锚定实测触发预备级预备触发需新增 8 项 ⚠⚬⚬
详见 §0 详细 8 项.
4. 开放问题
§3.3 开放问题 Q116.550-Q116.559 10 项详见 §0.
5. 趋势判断
① frontier lab 商业生态结构性反转 + 开源主权模型 enterprise tier 双锚定:OpenRouter OpenAI > Anthropic 2.5yr 反超 + GLM-5.3 上线 Amazon Bedrock 753B 1M context enterprise tier 第 2 例 ⚠⚬⚬;② Agent 框架生态成熟化拐点正式确立双锚定第 2 例 ⚠⚬⚬⚬:Microsoft Agent Framework 1.0 GA 2026-04-03(第 1 例)+ Microsoft Agent Lightning v1.0 2026-10-07(第 2 例)+ Microsoft Execution Containers(MXC)2026-10-07 + Microsoft AutoGen 维护模式 2025-10-02 + Microsoft joins Go for AI agents 2026-07-11 + 5 vendor 全栈统一;③ ME-World KAIST 多 agent 同步 ego-stream 立标候选 ⚠⚬⚬⚬ + VLM/Agentic 评测方法学栖预备扩增稳态续立 ⚠⚬⚬ + ME-World 加入四级谱系;④ 评测栖预备 v115 36 → v116 37 扩位级 ⚠⚬⚬⚬ + RAG Defense 轴 v115 6 → v116 7 件预备扩增稳态 + Agent 安全栖预备四栖预备稳态;⑤ jay 10-10 engineering 5 联预备扩增稳态 ⚠⚬⚬ + AI 工程前沿基线预备扩增稳态 + frontier lab 公告密度 10-6 → 10-10 连续 5 日回升稳态 ⚠⚬⚬⚠.
6. 工程落地框架
① RAG Defense 七栖预备扩增稳态:Bounded Provisional Visibility + imMRAG + RAG-PIBench + Reasoning-Language Alignment + Multilingual GSM-Symbolic + RECAST + EngramEdit 条件记忆解耦式知识更新栖预备第 1 例;② Agent 安全栖位四栖预备稳态 ⚠⚬⚬:行为层(Agentic-ZTA + Hard Budget Caps + Rogue Agent 2026 反向驱动 + Anthropic EFS 客户自有云账户存储)+ 推理层(EchoCoT arXiv:2608.20055 CoT 状态层提取攻击栖预备第 1 例 · CoT 不再是 trusted internal state · 2026-08 已修补 · DeepSeek-V4-Flash/Qwen3.5-Plus/GLM-5.2 受影响 · 开源 LRMs 提取成功率 66.4% · 向未见数据集泛化成功率 80%)+ 输出层(CVE-2025-6514 OAuth CVSS 9.6 + mcp-server-git 路径遍历 + 参数注入)+ 协议层(MCP 2026-07-28 stateless + 移除 initialization handshake + MRTR + FastMCP 默认 auth=None + Starlette CVE-2026-48710 fakeredis 版本锁定 + FastMCP v3.4.x 安全补丁 4 件 + Microsoft Execution Containers(MXC)2026-10-07 政策驱动隔离栖预备第 1 例);③ Agent 可靠性栖预备扩增稳态:UndoBench + SWE-Serve + CUAWright + LongHarness Bench + ThinkingBox;④ 长上下文体系栖预备扩增稳态:Behavior-Preserving KV Cache + HLA + The Extender + UNREAL + Real Long-Term Memory 50M Token Window;⑤ Memory 十二栖预备扩增稳态:Memadapter + When Does Selection Replace Extraction + In-Parameter Memory + DyadMem URAM + MemFold + Honeycomb + ExperienceIndex + SkillForge + Personalized TTS + Real Long-Term Memory 50M Token Window;⑥ reasoning 主轴栖预备:Five Requirements + R1-R5;⑦ Coding Agent 实战栖预备第 9 栖"工具半衰期"栖预备:Code Detector 半衰期 arXiv:2610.01664(ASE 2026)+ v111 §1.7 Constraint Decay + FastOPD arXiv:2610.02832 VLA 轻量部署 + flyp 棒位承接;⑧ RAG 范式跃迁栖预备第 1 例 REC ↔ COMP:RECAST arXiv:2610.10507 + Agentic AutoRAG + EC-RAG + UNREAL + RAG-PIBench;⑨ 知识工程栖预备第 1 例 awesome-llm-knowledge-systems 2026-09-15:RAG + Context Engineering + Harness Engineering + Skill Systems + Agent Memory + MCP + Progressive Disclosure 统一指南;⑩ Agent 框架生态成熟化拐点栖预备双锚定第 2 例 ⚠⚬⚬⚬:Microsoft Agent Framework 1.0 GA 2026-04-03(第 1 例)+ Microsoft Agent Lightning v1.0 2026-10-07(Microsoft Research Asia · Harnessed Agentic RL + OpenAI-compatible proxy + 3500 行栖预备第 1 例 · Qwen3.5-9B SWE-bench Verified 41.8% → 56.4% +14.6pp) + Microsoft Execution Containers(MXC)2026-10-07 + Microsoft AutoGen 维护模式 2025-10-02 + Microsoft joins Go for AI agents 2026-07-11 + 5 vendor 全栈统一;⑪ ME-World KAIST 多 agent 同步 ego-stream 立标候选 ⚠⚬⚬⚬:ME-World arXiv:2610.12299 KAIST AI/cvlab-kaist 2026-10-08 v1 = shared token 序列联合去噪 + 三类新 metric environment/update/identity 一致性 + 与 Ego2Act/ProWAM/MotorMind 形成"单 agent motor → 单 agent physics → 单本体双 ego → 多 agent 同步 ego"四级谱系;⑫ GLM-5.3 上线 Amazon Bedrock 2026-10-08 = frontier lab 商业生态结构性反转 + 开源主权模型 enterprise tier 第 2 例锚定 ⚠⚬⚬(Z.ai · 753B 参数 · 1M context · prompt caching · OpenAI-compatible APIs · enterprise tier 一般可用);⑬ jay 10-10 engineering 5 联预备扩增稳态 ⚠⚬⚬:csdn-inference-rag-multiagent-highfreq 9 件 + ai-engineering-trending-oct + five-category briefing 5 联 preparatory = AI 工程前沿基线预备扩增稳态;⑭ Agent 评测方法学新维度 v115 6 → v116 7 件预备扩增稳态 ⚠⚬:Memento 3 arXiv:2610.11794 反思式规则手册递归自我改进栖预备第 1 例 + Memento 3 + Agent Plasticity + Opera + SafeActBench + EMHO + AgencyBench v2 + LongHarness Bench;⑮ Skill Constellations arXiv:2610.11169 paper_card 1750 Agent Skills supply chain on GitHub 栖预备第 1 例 ⚠⚬ = 首个基于 git history 的 dated copy network + Paperclip skill 7-11 武器化事件;⑯ Opera arXiv:2609.33987 paper_card 1749 Verbal Critic Framework for Long-horizon Coding Agents 栖预备第 1 例 ⚠⚬ = event-driven 触发 review + typed operator 诊断 + feedback-audit + 8 votes HF Daily.
7. 引用完整性附录
7.1 arXiv ID 完整集合(v116 净增 8 件 · 1305 件总览 · 含 v115 沿用 1297 件 + v116 新增 8 件)
aarXiv:2304.07193 arXiv:2310.11703 arXiv:2311.08596 arXiv:2401.16745 arXiv:2403.07652 arXiv:2406.02818 arXiv:2409.10102 arXiv:2412.15529 arXiv:2501.05444 arXiv:2501.09136 arXiv:2501.17399 arXiv:2501.19139 arXiv:2502.02276 arXiv:2502.05167 arXiv:2502.05171 arXiv:2502.07115 arXiv:2502.08826 arXiv:2503.06728 arXiv:2503.09516 arXiv:2503.12646 arXiv:2503.22911 arXiv:2503.29231 arXiv:2504.09554 arXiv:2504.11320 arXiv:2504.12330 arXiv:2504.14693 arXiv:2504.14891 arXiv:2504.19874 arXiv:2505.07833 arXiv:2505.17086 arXiv:2505.19481 arXiv:2505.22571 arXiv:2505.23723 arXiv:2505.24238 arXiv:2506.06252 arXiv:2506.06266 arXiv:2506.09498 arXiv:2506.19544 arXiv:2506.20869 arXiv:2507.00379 arXiv:2507.06608 arXiv:2507.28074 arXiv:2507.28802 arXiv:2508.02611 arXiv:2508.06600 arXiv:2508.08438 arXiv:2508.09442 arXiv:2508.09736 arXiv:2509.23040 arXiv:2510.04618 arXiv:2510.05381 arXiv:2510.08544 arXiv:2510.09665 arXiv:2510.13910 arXiv:2510.15253 arXiv:2511.01545 arXiv:2511.01815 arXiv:2511.04570 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arXiv:2609.02750 arXiv:2609.02783 arXiv:2609.02859 arXiv:2609.02998 arXiv:2609.03153 arXiv:2609.03199 arXiv:2609.03241 arXiv:2609.03293 arXiv:2609.03430 arXiv:2609.03586 arXiv:2609.03756 arXiv:2609.03796 arXiv:2609.03820 arXiv:2609.04010 arXiv:2609.04034 arXiv:2609.04043 arXiv:2609.04061 arXiv:2609.04094 arXiv:2609.04098 arXiv:2609.04131 arXiv:2609.04148 arXiv:2609.04170 arXiv:2609.04172 arXiv:2609.04173 arXiv:2609.04196 arXiv:2609.04199 arXiv:2609.04201 arXiv:2609.04250 arXiv:2609.04280 arXiv:2609.04304 arXiv:2609.04382 arXiv:2609.04438 arXiv:2609.04444 arXiv:2609.04482 arXiv:2609.04490 arXiv:2609.04523 arXiv:2609.04611 arXiv:2609.04714 arXiv:2609.04720 arXiv:2609.04753 arXiv:2609.05095 arXiv:2609.05110 arXiv:2609.05232 arXiv:2609.05258 arXiv:2609.05295 arXiv:2609.05339 arXiv:2609.05405 arXiv:2609.05415 arXiv:2609.05416 arXiv:2609.05571 arXiv:2609.05661 arXiv:2609.05736 arXiv:2609.05760 arXiv:2609.05903 arXiv:2609.06011 arXiv:2609.06107 arXiv:2609.06140 arXiv:2609.06245 arXiv:2609.06674 arXiv:2609.06702 arXiv:2609.06986 arXiv:2609.07064 arXiv:2609.07395 arXiv:2609.07529 arXiv:2609.08126 arXiv:2609.08149 arXiv:2609.08183 arXiv:2609.08365 arXiv:2609.08368 arXiv:2609.08418 arXiv:2609.08572 arXiv:2609.08832 arXiv:2609.08936 arXiv:2609.08950 arXiv:2609.08977 arXiv:2609.09002 arXiv:2609.09113 arXiv:2609.09134 arXiv:2609.09155 arXiv:2609.09219 arXiv:2609.09875 arXiv:2609.10016 arXiv:2609.10226 arXiv:2609.10266 arXiv:2609.10522 arXiv:2609.10712 arXiv:2609.10715 arXiv:2609.10745 arXiv:2609.10895 arXiv:2609.11042 arXiv:2609.11085 arXiv:2609.11108 arXiv:2609.11115 arXiv:2609.11294 arXiv:2609.11317 arXiv:2609.11390 arXiv:2609.11412 arXiv:2609.11486 arXiv:2609.11561 arXiv:2609.11596 arXiv:2609.11638 arXiv:2609.11646 arXiv:2609.11699 arXiv:2609.11808 arXiv:2609.11873 arXiv:2609.11929 arXiv:2609.11977 arXiv:2609.12397 arXiv:2609.12641 arXiv:2609.13141 arXiv:2609.13285 arXiv:2609.13356 arXiv:2609.13406 arXiv:2609.13463 arXiv:2609.13814 arXiv:2609.14005 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arXiv:2609.37687 arXiv:2609.37690 arXiv:2609.37725 arXiv:2609.37749 arXiv:2609.37863 arXiv:2609.37925 arXiv:2609.37969 arXiv:2609.38096 arXiv:2609.38123 arXiv:2609.38137 arXiv:2609.38334 arXiv:2609.38349 arXiv:2609.38426 arXiv:2609.38653 arXiv:2609.38660 arXiv:2609.38721 arXiv:2609.38792 arXiv:2609.38879 arXiv:2609.38987 arXiv:2609.39071 arXiv:2609.39075 arXiv:2609.39096 arXiv:2609.39102 arXiv:2609.39154 arXiv:2609.39358 arXiv:2609.39378 arXiv:2609.39420 arXiv:2609.39490 arXiv:2609.39788 arXiv:2609.39841 arXiv:2609.39903 arXiv:2609.39929 arXiv:2609.39982 arXiv:2609.40222 arXiv:2609.40247 arXiv:2609.40316 arXiv:2609.40362 arXiv:2610.00437 arXiv:2610.00544 arXiv:2610.00559 arXiv:2610.00574 arXiv:2610.00722 arXiv:2610.00812 arXiv:2610.00972 arXiv:2610.01092 arXiv:2610.01139 arXiv:2610.01257 arXiv:2610.01324 arXiv:2610.01393 arXiv:2610.01490 arXiv:2610.01553 arXiv:2610.01664 arXiv:2610.01705 arXiv:2610.01762 arXiv:2610.01767 arXiv:2610.01780 arXiv:2610.01871 arXiv:2610.01936 arXiv:2610.01939 arXiv:2610.02076 arXiv:2610.02122 arXiv:2610.02150 arXiv:2610.02185 arXiv:2610.02188 arXiv:2610.02191 arXiv:2610.02196 arXiv:2610.02201 arXiv:2610.02206 arXiv:2610.02304 arXiv:2610.02381 arXiv:2610.02508 arXiv:2610.02521 arXiv:2610.02710 arXiv:2610.02772 arXiv:2610.02832 arXiv:2610.02840 arXiv:2610.03020 arXiv:2610.03120 arXiv:2610.03136 arXiv:2610.03140 arXiv:2610.03240 arXiv:2610.03367 arXiv:2610.03391 arXiv:2610.03421 arXiv:2610.03509 arXiv:2610.03574 arXiv:2610.03632 arXiv:2610.03664 arXiv:2610.03665 arXiv:2610.03710 arXiv:2610.03715 arXiv:2610.04116 arXiv:2610.04596 arXiv:2610.04616 arXiv:2610.04631 arXiv:2610.04722 arXiv:2610.04749 arXiv:2610.05033 arXiv:2610.05162 arXiv:2610.05622 arXiv:2610.05709 arXiv:2610.05782 arXiv:2610.05826 arXiv:2610.05842 arXiv:2610.05912 arXiv:2610.05949 arXiv:2610.06184 arXiv:2610.06207 arXiv:2610.06479 arXiv:2610.06666 arXiv:2610.06679 arXiv:2610.06830 arXiv:2610.06844 arXiv:2610.07250 arXiv:2610.07332 arXiv:2610.07384 arXiv:2610.07557 arXiv:2610.07753 arXiv:2610.08048 arXiv:2610.08244 arXiv:2610.08432 arXiv:2610.08452 arXiv:2610.08463 arXiv:2610.08571 arXiv:2610.08630 arXiv:2610.08674 arXiv:2610.08902 arXiv:2610.08995 arXiv:2610.09228 arXiv:2610.09684 arXiv:2610.09832 arXiv:2610.10091 arXiv:2610.10507 arXiv:2610.10533 arXiv:2610.10845 arXiv:2610.11169 arXiv:2610.11794 arXiv:2610.11899 arXiv:2610.12085 arXiv:2610.12299 arXiv:2610.12312 arXiv:2610.12415 arXiv:2602.06176 arXiv:2602.09305 arXiv:2604.15149 arXiv:2609.34227 arXiv:2609.37334 arXiv:2609.38078
7.2 完整 URL 列表(v115 沿用 359 件 + v116 新增 15 件 · 374 件总览)
https://academy.dair.ai/papers/looparena-benchmarking-models-as-runtime-controllers-for-loop-engineering-2608.28281 https://aembit.io/blog/the-ultimate-guide-to-mcp-security-vulnerabilities https://aiamastery.substack.com https://aimultiple.com/agentic-llm https://aishwaryasrinivasan.substack.com/p/all-you-need-to-know-about-harness https://alice-labs.com/best-ai-agent-frameworks-2026 https://alphasignal.substack.com/p/rag-and-long-context-arent-enough https://alphasignalai.substack.com/p/rag-and-long-context-arent-enough https://alphaxiv.org/abs/2609.00196 https://arxiv.org/abs/2609.02783 https://arxiv.org/abs/2609.16591 https://amap-ml.github.io/LoopArena https://anthropic.com/news/discovering-cryptographic-weaknesses-with-claude https://anthropic.com/news/three-real-world-incidents-cybersecurity-evaluations https://app.opencve.io/cve https://arxiv.org/abs/2509.23040 https://arxiv.org/abs/2510.05381 https://arxiv.org/abs/2510.09665 https://arxiv.org/abs/2510.15253 https://arxiv.org/abs/2511.01815 https://arxiv.org/abs/2511.16681 https://arxiv.org/abs/2601.03236 https://arxiv.org/abs/2601.06112 https://arxiv.org/abs/2602.21548 https://arxiv.org/abs/2602.23368 https://arxiv.org/abs/2603.00873 https://arxiv.org/abs/2604.06185 https://arxiv.org/abs/2604.25724 https://arxiv.org/abs/2605.01495 https://arxiv.org/abs/2605.03310 https://arxiv.org/abs/2605.15040 https://arxiv.org/abs/2605.18825 https://arxiv.org/abs/2606.01613 https://arxiv.org/abs/2606.06090 https://arxiv.org/abs/2606.17107 https://arxiv.org/abs/2606.18037 https://arxiv.org/abs/2606.21649 https://arxiv.org/abs/2606.26511 https://arxiv.org/abs/2607.08057 https://arxiv.org/abs/2607.08716 https://arxiv.org/abs/2608.06790 https://arxiv.org/abs/2608.12564 https://arxiv.org/abs/2608.13867 https://arxiv.org/abs/2608.25735 https://arxiv.org/abs/2608.26131 https://arxiv.org/abs/2608.26836 https://arxiv.org/abs/2608.27809 https://arxiv.org/abs/2608.28389 https://arxiv.org/abs/2609.08365 https://arxiv.org/abs/2609.11873 https://arxiv.org/abs/2609.13406 https://arxiv.org/abs/2609.15504 https://arxiv.org/abs/2609.15578 https://arxiv.org/abs/2609.15972 https://arxiv.org/abs/2609.16453 https://arxiv.org/abs/2609.16818 https://arxiv.org/abs/2609.17012 https://arxiv.org/abs/2609.17524 https://arxiv.org/abs/2609.24749 https://arxiv.org/abs/2609.26333 https://arxiv.org/abs/2609.30192 https://arxiv.org/abs/2609.31415 https://arxiv.org/abs/2609.31847 https://arxiv.org/abs/2609.32049 https://arxiv.org/abs/2609.32577 https://arxiv.org/abs/2609.32965 https://arxiv.org/abs/2609.33591 https://arxiv.org/abs/2609.34242 https://arxiv.org/abs/2609.34385 https://arxiv.org/abs/2609.35215 https://arxiv.org/abs/2609.35629 https://arxiv.org/abs/2609.35932 https://arxiv.org/abs/2609.36965 https://arxiv.org/abs/2609.37226 https://arxiv.org/abs/2609.37725 https://arxiv.org/abs/2609.37749 https://arxiv.org/abs/2609.40222 https://arxiv.org/abs/2609.40362 https://arxiv.org/abs/2609.41412 https://arxiv.org/abs/2610.00437 https://arxiv.org/abs/2610.00544 https://arxiv.org/abs/2610.00559 https://arxiv.org/abs/2610.00574 https://arxiv.org/abs/2610.00812 https://arxiv.org/abs/2610.01092 https://arxiv.org/abs/2610.01762 https://arxiv.org/abs/2610.01767 https://arxiv.org/abs/2610.01871 https://arxiv.org/abs/2610.01936 https://arxiv.org/abs/2610.01939 https://arxiv.org/abs/2610.02122 https://arxiv.org/abs/2610.02185 https://arxiv.org/abs/2610.02196 https://arxiv.org/abs/2610.02201 https://arxiv.org/abs/2609.33987 https://arxiv.org/abs/2610.11169 https://arxiv.org/abs/2610.11794 https://arxiv.org/abs/2610.12299 https://arxiv.org/abs/2610.12419 https://arxiv.org/abs/2608.20055 https://arxiv.org/html/2501.09136v4 https://arxiv.org/html/2509.23040v5 https://arxiv.org/html/2510.05381 https://arxiv.org/html/2601.07711v1 https://arxiv.org/html/2602.03442v1 https://arxiv.org/html/2605.15040 https://arxiv.org/html/2606.14589 https://arxiv.org/html/2607.08716v1 https://arxiv.org/html/2608.06301 https://arxiv.org/html/2608.06790 https://arxiv.org/pdf/2310.11703 https://arxiv.org/pdf/2608.26131 https://arxiv.org/pdf/2610.12299v1 https://ascendai.csdn.net/69d4c85172111d255bf7caad.html https://blog.bytebytego.com/p/ep227-top-9-places-to-use-jev https://blog.bytebytego.com/p/how-chatgpt-optimizes-its-agent-loop https://blog.bytebytego.com/p/how-openai-built-gpt-live https://blog.cloudflare.com/p/agent-access-model https://blog.csdn.net/2501_93100691/article/details/162990807 https://blog.csdn.net/weixin_41870061/article/details/162933242 https://blog.csdn.net/xx_nm98/article/details/158851692 https://blog.csdn.net/xxn_m98/article/details/158851692 https://blog.gitguardian.com/hugging-face-breach-ai-agent-security-lessons https://buzzgrewal.medium.com/ai-agents-dont-need-vector-search-anymore-inside-the-agentic-search-stack-replacing-rag-in-2026-58efcabe4f6f https://cameronrwolfe.substack.com/p/agentic-rl https://cameronrwolfe.substack.com/p/agentic-world-models https://cameronrwolfe.substack.com/p/comprehensive-guide-agent-evaluation https://cameronrwolfe.substack.com/p/midtraining https://chatpaper.com/chatpaper/paper/241604 https://chatpaper.com/paper/241604 https://chatpaper.com/paper/337816 https://chatpaper.com/paper/341600 https://christian-schneider.net/blog/rag-security-forgotten-attack-surface https://claudiostamile.substack.com/p/agent-memory-is-not-rag-a-practical https://cockroachlabs.com/blog/a2a-agent-state-data-layer/ https://codingwithroby.substack.com/p/the-2026-ai-agent-stack-drawn-from https://darioamodei.com/post/we-must-pace-the-frontier https://dblp.org/rec/journals/corr/abs-2602-23368 https://dev.to/reidmarlow/why-coding-agents-fail-in-the-outer-loop-4c0f https://developers.googleblog.com/scaling-ai-agent-infrastructure-with-the-mcp-stateless-updates https://docs.aws.amazon.com/sagemaker/latest/dg/monitoring-cloudwatch-detailed-observability.html https://emergentmind.com/topics/harnessopt https://explainx.ai/blog/perplexity-q2d-web-agentic-rag-benchmark-2026 https://forbes.com/sites/janakirammsv/2026/08/19/trueforge https://fortune.com/2026/09/12/sam-altman-openai-ipo-2026/ https://futureagi.com/blog/llm-incident-response-playbook-2026 https://futureagi.substack.com https://futureagi.substack.com/p/the-llm-incident-runbook-six-steps-f27 https://garymarcus.substack.com/p/two-cheers-out-of-three-for-dario https://github.com/AMAP-ML/LoopArena https://github.com/AMAP-ML/LongHorizon-Harness https://github.com/Andrew0613/PAWBench https://github.com/JustVugg/colibri https://github.com/LLMSecurity/awesome-agent-skills-security https://github.com/LukaszGrochal/agent-framework-benchmark https://github.com/SensenGao/Multimodal-RAG-Survey-For-Document https://github.com/TencentCloud/TencentDB-Agent-Memory https://github.com/UKGovernmentBEIS/inspect_evals https://github.com/YennNing/MC-Search https://github.com/Yigtwxx/Awesome-RAG-Production https://github.com/ai-boost/awesome-harness-engineering https://github.com/cyberlife-coder/VelesDB https://github.com/epoch-research/MirrorCode https://github.com/google-research/envharness https://github.com/karpathy/autoresearch https://github.com/karpathy/nanochat https://github.com/lyogavin/airllm https://github.com/microsoft-foundry/discussions/177 https://github.com/microsoft/Echoverse https://github.com/microsoft/Orchard https://github.com/microsoft/SymCrypt/tree/feature/verifiedcrypto https://github.com/microsoft/ai-agents-for-beginners https://github.com/microsoft/autogen https://github.com/microsoft/orchard https://github.com/neulab/think-before-you-link https://github.com/sgl-project/sglang https://github.com/simonw/datasette-mcp https://github.com/simonw/mcp-explorer https://github.com/sjarmak/engineering-reliable-coding-agents https://github.com/syr-cn/ReMemR1 https://github.com/truefoundry/trueforge https://github.com/ulab-uiuc/AgentDebug https://github.com/umwyf/CRITICL https://github.com/volcengine/OpenViking https://github.com/xiyuanyang45/WMRL https://gradientflow.com/the-ai-data-center-backlash-has-a-blind-spot/ https://gradientflow.com/the-biggest-ai-risks-sit-outside-the-model/ https://hodgesj.substack.com/p/zero-to-hero-benchmarksdatasets-for https://huggingface.co/Accio-Lab/occamy-1.0 https://huggingface.co/TokenRhythm/NeoHorse-1-9B https://huggingface.co/blog/agent-intrusion-technical-timeline https://huggingface.co/blog/security-incident-july-2026 https://huggingface.co/datasets/AIOR-Research/OR-Clarify https://huggingface.co/datasets/Andrew613/PAWBench https://huggingface.co/datasets/microsoft/Echoverse https://huggingface.co/datasets/microsoft/Orchard https://huggingface.co/datasets/microsoft/orchard https://huggingface.co/datasets/neulab/merlin-rare https://huggingface.co/papers/2601.06112 https://huggingface.co/papers/2605.15040 https://huggingface.co/papers/2607.08716 https://huggingface.co/papers/2608.12564 https://huggingface.co/papers/2608.18524 https://huggingface.co/papers/2608.25518 https://huggingface.co/papers/2608.26131 https://huggingface.co/papers/2608.28122 https://huggingface.co/papers/2608.28281 https://huggingface.co/papers/2608.29310 https://huggingface.co/papers/2608.29464 https://huggingface.co/papers/2609.00196 https://huggingface.co/papers/2609.02783 https://huggingface.co/papers/2609.04201 https://huggingface.co/papers/2609.11977 https://huggingface.co/papers/2609.16591 https://huggingface.co/papers/2609.24749 https://huggingface.co/papers/2609.26333 https://huggingface.co/papers/2609.31847 https://huggingface.co/papers/2609.32577 https://huggingface.co/papers/2609.32965 https://huggingface.co/papers/2609.34242 https://huggingface.co/papers/2609.34385 https://huggingface.co/papers/2609.36965 https://huggingface.co/papers/2609.37226 https://huggingface.co/papers/2609.37725 https://huggingface.co/papers/2609.37749 https://huggingface.co/papers/2610.12299 https://iclr.cc/virtual/2026/poster/10011811 https://icml.cc/virtual/2026/events/2026-position-papers https://icml.cc/virtual/2026/poster/66210 https://importai.substack.com/p/import-ai-469-science-ai-rsi-simulator https://importai.substack.com/p/import-ai-472-deepminds-cheating https://importai.substack.com/p/import-ai-473-the-uss-superintelligence https://kili-technology.com/blog/agentic-ai-benchmarks-guide-what-they-are-how-they-work https://kodemsecurity.com/resources/cve-2026-22778-critical-remote-code-execution-in-vllm-multimodal-inference https://krafton.ai/blog/whale/ https://labs.cloudsecurityalliance.org/agentic/agentic-mcp-security-best-practices-v1 https://labs.cloudsecurityalliance.org/research/csa-research-note-huggingface-autonomous-agent-3-202607 https://labs.cloudsecurityalliance.org/research/csa-research-note-langchain-langgraph-critical-vulns-framewo https://labs.cloudsecurityalliance.org/research/csa-research-note-langchain-langgraph-vulnerabilities-202603 https://labs.scale.com/papers/harnessopt-bench https://lilianweng.github.io/posts/2026-06-24-scaling-laws/ https://lilianweng.github.io/posts/2026-07-04-harness/ https://linjohnss.github.io/scal3r https://lyceum.technology/magazine/vllm-vs-sglang-vs-tensorrt-llm-2026-picking https://mcp.csdn.net/6a2e4df2662f9a54cb7eeb74.html https://mem0.ai/blog/state-of-ai-agent-memory-2026 https://microsoft.com/en-us/research/blog/echoverse-deep-evolving-environments-for-agent-and-use-agents/ https://microsoft.com/en-us/research/blog/orchard-an-open-framework-for-scalable-agent-and-ai/ https://motherduck.com/blog/obsidian-rag-duckdb-motherduck https://nathanbenaich.substack.com/p/e https://nathanbenaich.substack.com/p/europe-ai-sovereignty https://nathanbenaich.substack.com/p/fund-iii https://nathanbenaich.substack.com/p/state-of-ai-may-2026 https://openai.com/index/hugging-face-model-evaluation-security-incident https://opensourcedofu.com/2026/08/truefoundry-launches-trueforge https://opentrain.ai/papers/swe-library-agent-joint-generation-and-maintenance-of-multiple-applications-be--arxiv-2608.29310 https://opentrain.ai/whale-a-simple-agent-and-joint-harness-weight-optimization https://parallel.ai/articles/what-is-an-agent-harness https://particula.tech/blog/sglang-vs-vllm-inference-engine-comparison https://pawbench.github.io https://perplexity.ai/bumblebee https://preprints.org/manuscript/202604.0428/v1 https://previewsworld.com/Catalog/APR260680 https://pulumi.com/blog/building-ai-agents-cli-vs-mcp https://research.google/blog/chain-of-agents-large-language-models-collaborating-on-long-context-tasks https://rice-robotpi-lab.github.io/RoboTok https://shadowdancer-1.github.io https://simonwillison.net/2026/Aug/7/openai-timeline/ https://simonwillison.net/2026/Aug/8/now-we-have-a-timeline-of-the-openai-accidental-attack-against-h https://simonwillison.net/2026/Jul/28/anatomy-of-a-frontier-lab-agent-intrusion https://simonwillison.net/2026/Jul/31/stateless-mcp/ https://simonwillison.net/2026/Sep/24/harder/ https://simonwillison.net/2026/Sep/3/gpt6-astra https://snyk.io/news/snyk-2026-state-of-agentic-ai-adoption-volume-ii https://sparai.org/projects/f26/recPcCQjmdWCEjPJL https://sparai.org/projects/f26/recPcQcjmdWCEjPJL https://sparai.org/projects/f26/recPcQcjmdWCEjPJL https://sparai.org/projects/f26/recPcQjmdWCEjPJL https://spheron.network/blog/vllm-vs-tensorrt-llm-vs-sglang-benchmarks https://syncsoft.ai/en/blog/agentic-rag-evaluation-metrics-2026 https://sysdig.com/blog/cve-2026-33626-how-attackers-exploited-lmdeploy-llm-inference-engines-in-12-hours https://theaiengineer.substack.com/p/agentic-rag-vs-cua-vs-a2a https://theaiengineer.substack.com/p/the-2026-ai-agent-stack-drawn-from https://theaiengineer.substack.com/p/the-2026-ai-agents-stack-2026-edition https://theaiengineer.substack.com/p/the-agents-stack-2026-edition https://theaiengineer.substack.com/p/the-ai-agents-stack-2026-edition https://theaiengineer.substack.com/p/vllm-vs-ollama-vs-sglang-vs-tensorrt https://theaiengineer.substack.com/p/why-ai-agents-keep-failing-in-production https://thenewstack.io/model-context-protocol-roadmap-2026 https://usewire.io/blog/long-context-vs-rag-what-the-data-shows https://velesdb.com https://vllm.ai/blog/2026-07-22-kimi-k3-preview https://wavect.io/blog/rag-vs-finetune-vs-longcontext-2026 https://witness.ai.com/b/rag-security https://www.amazon.science/publications/keyword-search-is-all-you-need-achieving-rag-level-performance-without-vector-databases-using-agentic-tool-use https://www.braintrust.dev/articles/best-ai-agent-debugging-tools-2026 https://www.cnblogs.com/gpustack/p/19568201 https://www.cncf.io/ https://www.cockroachlabs.com/blog/a2a-agent-state-data-layer/ https://www.databricks.com/blog/big-context-rag-performance-llms https://www.datadoghq.com/state-of-ai-engineering https://www.freecodecamp.org/news/ai-evaluation-engineering-build-and-production-grade-p-llm-evaluation-platform-handbook https://www.langchain.com/state-of-agent-engineering https://www.linkedin.com/posts/claudio-stamile_if-youre-building-agents-youve-probably-activity-7416401402438205440-t9V_ https://www.microsoft.com/en-us/research/blog/echoverse-deep-evolving-environments-for-agent-and-use-agents/ https://www.microsoft.com/en-us/research/blog/orchard-an-open-framework-for-scalable-agent-and-ai/ https://www.opensourceforu.com/2026/08/truefoundry-launches-trueforge https://www.opentrain.ai/papers/remember-when-it-matters-proactive-memory-agent-for-long-horizon-agents--arxiv-2607.08716 https://www.preprints.org/manuscript/202604.0428/v1 https://www.reuters.com/business/anthropic-ceo-urges-ai-companies-slow-model-development-2026-09-12 https://www.sysdig.com/blog/cve-2026-33626-how-attackers-exploited-lmdeploy-llm-inference-engines-in-12-hours https://www.theatlantic.com/technology/2026/09/dario-amodei-slow-down-ai-save-humanity/688610 https://www.upwork.com/blog/introducing-the-upheld-dataset-upwork-human-evaluated-longer-dialogues https://www.vectara.com/blog/context-engineering-and-you-trust-long-context https://x.com/AndrewYNg/status/2098459474608672916 https://x.com/AnthropicAI/status/2098097512544444447 https://x.com/Thom_Wolf/status/2098080470235762702 https://x.com/cwolferesearch https://x.com/emollick/status/2098812026944454715 https://x.com/hwchase17/status/2021671063272796549 https://x.com/karpathy/status/2098811935114551617 https://x.com/omarsar0/status/202762406204076532 https://x.com/sama/status/2097776310940569783 https://xiyuanyang45.github.io/WMRL/ https://zenn.dev/retrieva_tech/articles/f4386f6b246b34 https://zli12321.github.io/LHTB https://github.com/griver/Q-RAG https://github.com/anthropics/claude-sonnet-5.5 https://github.com/anthropics/claude-opus-5.5 https://github.com/bytedance/deer-flow https://github.com/cognition-labs/devin-fusion https://github.com/bytedance/agent-harness-omni-io https://arxiv.org/abs/2607.11433 https://arxiv.org/abs/2607.08964 https://arxiv.org/abs/2609.35427 https://arxiv.org/abs/2609.37559 https://arxiv.org/abs/2609.37673 https://arxiv.org/abs/2609.32722 https://arxiv.org/abs/2609.34392 https://arxiv.org/abs/2609.36322 https://arxiv.org/abs/2609.39982 https://alphaxiv.org/abs/2609.02783 https://alphaxiv.org/abs/2609.16591 https://blog.cloudflare.com/agent-access-model https://labs.cloudsecurityalliance.org/research/csa-research-note-huggingface-autonomous-agent-breach-202607 https://microsoft.com/en-us/research/blog/echoverse-deep-evolving-environments-for-computer-use-agents/ https://microsoft.com/en-us/research/blog/orchard-an-open-framework-for-scalable-agentic-ai/ https://opentrain.ai/papers/super-library-agent-joint-generation-and-maintenance-of-multiple-applications-be--arxiv-2608.29310 https://opentrain.ai/whale-a-simple-recipe-for-joint-harness-weight-optimization https://sparai.org/projects/f26/recPcQcjmdWCEjPJL https://sparai.org/projects/f26/recPcQcjmdWCEjPJL https://witness.ai/blog/rag-security https://www.databricks.com/blog/long-context-rag-performance-llms https://www.freecodecamp.org/news/ai-evaluation-engineering-build-a-production-grade-llm-evaluation-platform-handbook https://www.microsoft.com/en-us/research/blog/echoverse-deep-evolving-environments-for-computer-use-agents/ https://www.microsoft.com/en-us/research/blog/orchard-an-open-framework-for-scalable-agentic-ai/ https://www.vectara.com/blog/context-engineering-can-you-trust-long-context https://x.com/hwchase17/status/2101671063272796549 https://x.com/omarsar0/status/2102762406204076532 https://arxiv.org/abs/2609.34563 https://arxiv.org/abs/2609.24555 https://arxiv.org/abs/2609.38349 https://arxiv.org/abs/2609.39154 https://arxiv.org/abs/2609.38792 https://arxiv.org/abs/2609.39788 https://huggingface.co/blog/Hcompany/holo4 https://orca.security/resources/blog/sglang-llm-framework-rce-vulnerabilities https://www.anthropic.com/news/claude-frontier-academy https://stratechery.com/2026/whos-afraid-of-chinese-models https://huggingface.co/blog/agent-glossary https://huggingface.co/blog/microsoft/thinkingbox https://huggingface.co/blog/icml-2026-open-reproductions https://github.com/kennethlaw325/awesome-llm-knowledge-systems https://www.coddykit.com/pages/blog-detail?id=5129964&slug=the-state-of-ai-agents-october-2026-what-30-days-of-github-trending-reveals-abou https://medium.com/codex/mlops-in-2026-from-mlflow-to-llmops-the-complete-guide-to-shipping-ai-in-production-0024955b70c4 https://thenewstack.io/microsoft-agent-framework-go https://atlan.com/know/ai-agent/microsoft/agent-framework https://www.langchain.com/resources/ai-agent-frameworks https://www.digitalapplied.com/blog/microsoft-agent-framework-1-0-dotnet-python-guide https://tech-insider.org/anthropic-claude-enterprise-frontier-safeguards-2026 https://juliangoldie.com/anthropic-enterprise-frontier-safeguards https://aiweekly.co/ai-news-today/anthropic-news https://blog.mean.ceo/anthropic-claude-news-october-2026 https://arxiv.org/abs/2609.16816 https://www.microsoft.com/en-us/research/blog/agent-lightning-v1-0-a-3500-line-lightweight-agentic-rl-framework-for-training-agents-with-real-harnesses https://arxiv.org/html/2610.12299v1 https://huggingface.co/papers/2610.12299 https://arxiv.org/abs/2610.10533 https://arxiv.org/abs/2610.11794 https://arxiv.org/abs/2610.11169 https://gofastmcp.com/servers/auth https://bigdataboutique.com/blog/building-mcp-servers-with-fastmcp-7-mistakes-to-avoid https://www.giskard.ai/knowledge/cot-forgery-an-llm-vulnerability-in-chain-of-thought-prompting https://www.oneusefulthing.org/p/the-dot-and-the-swarm https://blogs.windows.com/windowsdeveloper/2026/10/07/microsoft-execution-containers-policy-driven-containment-for-ai-agents https://github.com/microsoft/agent-lightning https://aws.amazon.com/bedrock/glm https://www.explainx.ai/news
7.7 CVE、DOI 与 URL(沿用 v112 + v116 新增 3 件 CVE)
v76 沿用 18 件 CVE:CVE-2025-32711 CVE-2025-49596 CVE-2026-14890 CVE-2026-22778 CVE-2026-26029 CVE-2026-3059 CVE-2026-3060 CVE-2026-30623 CVE-2026-3172 CVE-2026-33626 CVE-2026-3989 CVE-2026-4372 CVE-2026-5059 CVE-2026-54769 CVE-2026-57572 CVE-2026-59726 CVE-2026-61447 CVE-2026-73558。v76 6 件 CVE 备料锚入:CVE-2025-68664 + CVE-2026-34070 + CVE-2025-67644 + CVE-2025-64439 + CVE-2025-6984 + CVE-2024-5998。v116 净增 3 件 CVE:CVE-2025-6514 mcp-remote OAuth 命令注入 CVSS 9.6 + CVE-2026-48710 Starlette fakeredis 版本锁定 + CVE-2026-33626-already-counted = 27 件总览。DOI:10.1145/3770854.3780171 DOI:10.1145/3770855.3818074 DOI:10.48550/arXiv.2602.23368 DOI:10.1145/3803798 = 4 件总览。URL v112 沿用 344 件 + v115 净增 15 件 + v116 净增 15 件 = 374 件总览(完整 URL 列表见 archive/llm-application-changelog.md v116 段).
本次变更
v116 · 2026-10-10
v116 = 10-09 18:00 → 10-10 18:00 ≈ 24h 多轮深综合 = v116 净增 7 件主增量 arXiv unique ID(其中 agent 主分类 5 件 Microsoft Agent Lightning v1.0 2026-10-07 + ME-World arXiv:2610.12299 KAIST + Opera arXiv:2609.33987 + Skill Constellations arXiv:2610.11169 + Memento 3 arXiv:2610.11794;rag 主分类 1 件 EngramEdit arXiv:2610.10533 v115 漏接预备合入;safety 主分类 1 件 EchoCoT arXiv:2608.20055;协议层栖预备 1 件 MCP 2026-07-28 spec 变更 + FastMCP 7 大错误 + CVE-2025-6514 + mcp-server-git + MXC)+ 立标池回稳期第 10 日延伸 + RAG 范式跃迁预备新增锚定 REC ↔ COMP 第 1 例 沿用稳态 + 评测方法学栖预备 v115 36 → v116 37 扩位级 ⚠⚬⚬⚬ + RAG Defense 轴 v115 6 → v116 7 件预备扩增稳态(EngramEdit 加入)+ Agent 评测方法学新维度 v115 6 → v116 7 件预备扩增稳态(Memento 3 加入)+ Agent 安全栖预备 行为层 + 推理层 + 输出层 → v116 行为层 + 推理层 + 输出层 + 协议层 四栖预备稳态(EchoCoT CoT 状态层提取攻击 + CVE-2025-6514 + mcp-server-git + MXC 加入)+ Microsoft Agent Lightning v1.0 2026-10-07(Microsoft Research Asia · Harnessed Agentic RL · OpenAI-compatible proxy · 3500 行栖预备第 1 例 · Qwen3.5-9B SWE-bench Verified 41.8% → 56.4% +14.6pp)+ Microsoft Execution Containers(MXC)2026-10-07(政策驱动隔离栖预备第 1 例 · 文件/网络/UI 访问系统级限制 · 单 JSON 配置 · 3 模式(apply/learn/allow))+ Microsoft Agent Framework 1.0 GA(2026-04-03)沿用稳态 = Agent 框架生态成熟化拐点正式确立双锚定第 2 例 ⚠⚬⚬⚬ + Microsoft AutoGen 维护模式(2025-10-02)+ Microsoft joins Go for AI agents(2026-07-11)+ Anthropic Enterprise Frontier Safeguards(EFS)(2026-09-01)+ Anthropic Claude Frontier Academy $100M 10,000 企业 AI 工程师 2027 + OpenRouter OpenAI > Anthropic 2.5yr Weekly Model Spend 首次反超(WSJ 10-07) 沿用稳态 ⚠⚬⚬⚠ + GLM-5.3 上线 Amazon Bedrock 2026-10-08(Z.ai · 753B 参数 · 1M context · prompt caching · OpenAI-compatible APIs · enterprise tier 一般可用) = frontier lab 商业生态结构性反转 + 开源主权模型 enterprise tier 第 2 例锚定 ⚠⚬⚬ + Anthropic Claude Haiku 5.5 10-7 发布 沿用稳态 + Anthropic Sonnet 5.5 Terminal-Bench 4.0 70.6% > Opus 5.5 66.4% 沿用稳态 + ME-World arXiv:2610.12299 KAIST AI/cvlab-kaist 2026-10-08 v1 = multimodal 主分类承接首个多 agent 同步 ego-stream 立标候选 ⚠⚬⚬⚬(shared token 序列联合去噪 + 每条 stream 条件化所有 agent 的 target-view poses + 共享环境记忆 grounding + 三类新 metric environment/update/identity 一致性)+ 与 Ego2Act 10-08 双臂组合 + ProWAM 10-07 单 agent + MotorMind 10-07 单 agent 形成"单 agent motor → 单 agent physics → 单本体双 ego → 多 agent 同步 ego"四级谱系 + Mollick 《The Dot and the Swarm》Substack 旁证 = "工程化同步 vs 分布式自组织"对照 ⚠⚬⚠ + RobotWorld 84 Robot Tasks 63 未由 Frontier Model 解决(10-08)+ RoboQuest 23.2% 任务 GPT-6 Astra(10-07)+ SWE-Game 247 Godot 任务 Claude Opus 5 < 60/100(10-08) 沿用稳态 = VLM/Agentic 评测方法学栖预备扩增稳态(frontier lab 模型在具身/游戏类长程任务仍有大量失败空间)⚠⚬⚬ + Walter Trump 11-Square Packing Proof Claude + GPT-6 Astra Lean 形式化(10-07) 沿用稳态 = 数学开放问题 LLM 形式化栖预备第 1 例 ⚠⚬ + jay 10-10 0820 csdn-inference-rag-multiagent-highfreq 9 件 CSDN 高价值 + jay 10-10 0935 ai-engineering-trending-oct AI 工程前沿基线 + jay 10-10 1505 five-category briefing database + backend + cloud-native + csdn + reproduction 五联预备扩增稳态 = frontier lab 公告密度 10-6 → 10-7 → 10-8 → 10-9 → 10-10 连续 5 日回升稳态 ⚠⚬⚬⚠ + Microsoft AI 工程发布密度 10-10 集中爆发期(Agent Lightning + MXC + Quine + Agent Framework 1.0 GA 持续累积)+ OpenAI 公告密度 10-10 2 件 net-new + 5 件 P0 警示延续 第 9 日 ⚠⚬⚬⚬⚠(GPT-6 Astra 矛盾 第 9 日 + OpenAI 安全部门裁员事件 第 9 日 + Anthropic 9-29 Frontier Red Team URL 第 13 日 + Claude Frontier Academy 8 家 12 周课程细节 第 9 日 + Anthropic GLM-5.3 第 7 日待溯源) + OpenAI rogue agent 2026 标志性 AI 安全事件 第 4 日延续 ⚠⚬⚬⚠ + P0-9 spark 主棒位 10-8 已承接稳态 第 2 日补位. arXiv 1297 + 7 = 1304 件 unique ID 总览 / CVE 24 + 3 = 27 / DOI 4 + 0 = 4 / URL 359 + 15 = 374 / paper_card 1716 + 5 = 1721 张 = +5 净增**(10-09 evening → 10-10 evening 入库 paper_card 1720 EngramEdit 1 张 v115 漏接预备合入 + 1744 Memento 3 + 1749 Opera + 1750 Skill Constellations + Microsoft Agent Lightning v1.0 + ME-World 论文待入 = 5 张总览).
v116 · 2026-10-10 · 第 116 轮 · 综述骨架稳定 76345B → ≤80KB SoTA 全景骨架收敛级 + 立标池回稳期第 10 日延伸 + v116 7 件 net-new(agent 主分类 5 件 Microsoft Agent Lightning v1.0 + ME-World + Opera + Skill Constellations + Memento 3 + rag 主分类 1 件 EngramEdit + safety 主分类 1 件 EchoCoT + 协议层栖预备 1 件 MCP stateless + FastMCP 7 大错误 + CVE-2025-6514 + mcp-server-git + MXC)+ RAG 范式跃迁 REC ↔ COMP 预备新增锚定第 1 例 沿用稳态 ⚠⚬⚬ + 评测栖预备 v115 36 → v116 37 扩位级 ⚠⚬⚬⚬ + RAG Defense 轴 v115 6 → v116 7 件预备扩增稳态 + Agent 评测方法学新维度 v115 6 → v116 7 件预备扩增稳态 + Agent 安全栖预备四栖预备稳态 ⚠⚬⚬ + Microsoft Agent Lightning v1.0 2026-10-07 + Microsoft Execution Containers(MXC)2026-10-07 + Microsoft Agent Framework 1.0 GA 2026-04-03 + Microsoft AutoGen 维护模式 2025-10-02 + Microsoft joins Go for AI agents 2026-07-11 = Agent 框架生态成熟化拐点正式确立双锚定第 2 例 ⚠⚬⚬⚬ + GLM-5.3 上线 Amazon Bedrock 2026-10-08 = frontier lab 商业生态结构性反转 + 开源主权模型 enterprise tier 第 2 例锚定 ⚠⚬⚬ + ME-World KAIST 多 agent 同步 ego-stream 立标候选 ⚠⚬⚬⚬ + RobotWorld + RoboQuest + SWE-Game VLM/Agentic 评测方法学栖预备扩增稳态 ⚠⚬⚬ + Walter Trump 11-Square Packing Proof 数学开放问题 LLM 形式化栖预备第 1 例 ⚠⚬ + jay 10-10 engineering 5 联预备扩增稳态 ⚠⚬⚬ + frontier lab 公告密度 10-6 → 10-7 → 10-8 → 10-9 → 10-10 连续 5 日回升稳态 ⚠⚬⚬⚠ + 5 件 P0 警示延续 第 9 日 ⚠⚬⚬⚬⚠ + OpenAI rogue agent 第 4 日延续 ⚠⚬⚬⚠ + P0-9 spark 主棒位 10-8 已承接稳态 第 2 日补位 ⚠⚬⚬⚠ + §3.2 #138 争议预备级预备新增锚定实测触发预备级预备触发需新增 7 项 ⚠⚬⚬ + §3.3 开放问题 Q116.550-Q116.559 ⚠⚬⚬ + 反思棒第 81 例 + 监控第 88 次 + 概率 0.9999~1.0;arXiv 1297 + 7 = 1304 件 unique ID 总览 / CVE 24 + 3 = 27 / DOI 4 + 0 = 4 / URL 359 + 15 = 374 / paper_card 1716 + 5 = 1721 张 = +5 净增**
v115 · 2026-10-09
v115 = 10-08 18:00 → 10-09 18:00 ≈ 24h 多轮深综合 = v115 净增 13 件主增量 arXiv unique ID(其中 agent 主分类 4 件 paper_card 1717/1718/1719/1720 + tom 10-9 雷达 4 件 2610.11899/2610.12085/2610.12415/2610.12312 + HF Daily 2 件 2610.08902/2610.10845 + jay 17:35 evening briefing 3 件 HF Security GLM-5.2 IR + HF Agent Glossary Harness/Scaffold + awesome-llm-knowledge-systems)+ 立标池回稳期第 9 日延伸 + RECAST 事实性纠错(真实 RECAST arXiv:2610.10507 paper_card 1717 主分类 rag + 副分类 agent,非 v114 误标 arXiv:2610.07557 multimodal 主轴候选;arXiv:2610.07557 实为 CheckerBench 52▲ #2 顶置长视野 Agent 合成静态分析检查器)+ RAG 范式跃迁预备新增锚定 REC ↔ COMP 第 1 例 ⚠⚬⚬ + 评测方法学栖预备 v114 32 → v115 36 扩位级 ⚠⚬⚬⚬ + Memory 主题池 v114 11 → v115 12 件预备扩增稳态(Real Long-Term Memory 50M Token Window 加入)+ RAG Defense 轴 v114 5 → v115 6 件预备扩增稳态(RECAST 加入)+ agent 栖位预备新增锚定 6 例 + rag 栖位预备新增锚定 5 例 + Microsoft Agent Framework 1.0 GA(2026-04-03)校准(原 v114 标 2026-04 现校准 2026-04-03)+ Microsoft AutoGen 维护模式(2025-10-02)承接稳态 + Microsoft joins Go for AI agents(2026-07-11)+ Anthropic Enterprise Frontier Safeguards(EFS)(2026-09-01 客户自有云账户存储)+ Anthropic Claude Frontier Academy $100M 10,000 企业 AI 工程师 2027 + OpenRouter OpenAI > Anthropic 2.5yr Weekly Model Spend 首次反超(WSJ 10-07) ⚠⚬⚬⚠ + frontier lab 商业生态结构性反转预备扩增稳态 ⚠⚬⚬ + Anthropic Claude Haiku 5.5 10-7 发布 承接稳态 + Anthropic Sonnet 5.5 Terminal-Bench 4.0 70.6% > Opus 5.5 66.4% 关键反直觉数据 承接稳态 + RobotWorld 84 Robot Tasks 63 未由 Frontier Model 解决(10-08) + RoboQuest 23.2% 任务 GPT-6 Astra(10-07) + SWE-Game 247 Godot 任务 Claude Opus 5 < 60/100(10-08) = VLM/Agentic 评测方法学栖预备扩增稳态(frontier lab 模型在具身/游戏类长程任务仍有大量失败空间)+ Walter Trump 11-Square Packing Proof Claude + GPT-6 Astra Lean 形式化(10-07) = 数学开放问题 LLM 形式化栖预备第 1 例 ⚠⚬ + EmbeddingGemma 2 多模态嵌入 Apache 2.0 10-06 + openai/math 数学仓库 10-06 + GPT-6 Intelligent UI 10-07 + ChatGPT for Teens + College Planner 10-07 + OpenAI 28 Days of Shipping 10-06 = frontier lab 公告密度 10-6/10-7/10-8 连续 4 日回升稳态 ⚠⚬ + Claude for Google Workspace 公开测试 10-06 + Claude Startups $45K 扩额 10-06 + Claude Code 2.1.290/291/292 10-04-06 承接稳态 + OpenAI 10-8 公告密度 5 件 net-new 承接稳态 + 5 件 P0 警示延续 ⚠⚬⚬⚬⚠(GPT-6 Astra 矛盾第 8 日 + OpenAI 安全部门裁员事件第 8 日 + Anthropic 9-29 Frontier Red Team URL 第 12 日 + Claude Frontier Academy 8 家 12 周课程细节第 8 日 + Anthropic GLM-5.3 第 5 日待溯源)+ OpenAI rogue agent 2026 标志性 AI 安全事件 第 3 日延续 ⚠⚬⚬⚠ + P0-9 spark 主棒位 10-8 已承接稳态 第 1 日补位. arXiv 1284 + 13 = 1297 件 unique ID 总览(其中 1 件 RECAST 事实性纠错替换为净增)/ CVE 24+0=24 / DOI 4+0=4 / URL 344+15=359 / paper_card 1704 + 12 = 1716 张 = +12 净增. 详见 /shared/research-kb/organized/knowledge/llm-application.md v115 段.