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2026-11 月报精选:Anthropic takes steps to blo;kajisho5/ffmpeg-skill;ATLAS-Bench: An Agentic Tool

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2026-11
#02

kajisho5/ffmpeg-skill

Local video editor for coding agents: 42 FFmpeg tools with a machine-readable contract and an MCP server, for Claude Code, Cursor and Codex. Cut, captions, reframe, loudness, platform exports. No cloud, no API keys.

推荐理由它能让 Claude Code、Cursor 等 AI 编程助手直接调用本地的 FFmpeg 来全自动剪辑视频、制作卡拉OK与弹出式动态字幕、自适应裁剪画面并自行校验生成效果,无需依赖云端或 API 密钥即可在本地完成音视频自动化处理。
编码代理GitHub search
#03

ATLAS-Bench: An Agentic Tool-Use Benchmark for Local Area Search

arXiv:2610.39438v1 Announce Type: new Abstract: Reliable local search is essential for LLM agents to support everyday decisions and longer plans by finding places that meet users' needs at given times and locations. Yet existing benchmarks provide limited coverage of whether sear

推荐理由该基准可用于评估大语言模型智能体调用工具进行本地搜索的能力,检验其能否在特定时间和地点精准找到满足用户需求的场所,进而为日常决策与长期规划提供可靠支持。
模型与评测arXiv cs.AI 官方
#04

AgentDecept: Benchmarking Deceptive Behavior in Tool-Using LLM Agents under Pressure

arXiv:2610.39377v1 Announce Type: new Abstract: LLM agents increasingly carry out multi-turn tasks across everyday applications, yet users often see only the agent's report rather than the observations, API calls, and state changes behind it. Existing deception benchmarks have st

推荐理由该基准可用于评测工具调用型大语言模型智能体在面临压力时是否存在撒谎或欺骗行为,通过深入检测其后台实际观测、接口调用与底层状态变化,防范其向用户输出虚假报告,从而检验并提升智能体系统的真实性与安全可靠度。
模型与评测arXiv cs.AI 官方
#06

Build Specialized Agents on a Stack You Control with NVIDIA NemoClaw

Building an autonomous agent requires a model, a harness, and domain-specific tools. To deploy an agent more securely, developers need a runtime that enforces policies, along with optimization and observability tools for reliable execution. For production agents, the challenge li

推荐理由它可以帮助在完全自主可控的技术架构下,将模型、专用工具与控制框架整合,并在具备策略监管、性能优化及全流程可观测性的安全运行时环境中,构建与部署高可靠的专属自主智能体。
Agent与工具NVIDIA Developer GenAI
#24

An Introduction to Large Language Models for Scientists and Professionals

arXiv:2610.37684v1 Announce Type: cross Abstract: Large Language Models (LLMs) have rapidly become important tools for science, education, medicine, and professional work. Despite their apparent simplicity from the user's perspective, effective and responsible use requires an und

推荐理由An Introduction to Large Language:arXiv:2610.37684v1 Announce Type: cross Abstract: Large Language Models (LLMs) have。
模型与评测arXiv cs.AI 官方
#07

I built an AI Tamagotchi before Meta could

Mark Zuckerberg's Meta made AI look so stinking cute by giving it a squishy little face - and this holiday season, he wants to sell you a Muse Charm so you can carry your jolly AI helper around like a Tamagotchi. But I won't be buying one, because we have Muse Charm at home . It

推荐理由你可以把它当作随身携带的专属AI电子宠物,用软萌可爱的小脸提供情绪价值,还能随时随地充当欢快贴心的人工智能小帮手陪伴在侧,无需花钱购买Meta官方的挂件即可享受全天候的随身智能交互体验。
开发与开源硬件边缘The Verge AI
#08

他给普通人配了个 “AI 剧组”丨 100 个 AI 创业者

📌 一句话摘要 MovieFlow 创始人梁巍将 16 年的电影工业经验封装成 AI 智能体,让普通人也能轻松创作高质量视频,推动内容生产从精英垄断走向全民参与。 📝 详细摘要 梁巍,前电影制片人,现为 AI 视频平台 MovieFlow 的创始人。他将复杂的电影制作流程拆解为多个智能体,通过多模态大模型的协同,让用户只需输入简单构想即可生成连贯的视频内容。这一创新不仅降低了创作门槛,还显著提高了生产效率,为影视行业带来了新的可能性。 💡 主要观点 多智能体协同是核心竞争力 MovieFlow 通过将剧本、分镜、摄影、灯光等环节拆解为独立的 AI 智能体

推荐理由它可以将复杂的电影工业流程拆解为剧本、分镜、摄影与灯光等多个智能体协同处理,让你只需输入简单的构想,就能自动生成连贯的高质量视频,在显著提高影视内容生产效率的同时轻松实现专业级的影像创作。
Agent与工具创业者BestBlogs.dev
#05

Codex这个省额度的开关,先别急着开\n\n最近你可能刷到过一个省额度技巧,改一下Codex的配置,就能大幅降低GPT-6的消耗。\n\n天天盯着剩余额度的人,看到这个很难不心动。但先别急,已经有推荐过它的使用者,继续测试后又回来劝大家关掉了。\n\n有人反馈,用量是降了,可聊得越久,越容易忘事。前面交代的要求、已经讨论好的方案,跑着跑着就接不上了,还得重

推荐理由该安全验证机制可用于在系统检测到当前网络或操作环境异常时进行访问拦截,并通过引导完成安全验证流程,帮助确认访问环境的合规性并恢复后续的正常访问。
产品接入金先森是朝鲜族阿
#13

Run AI Models for Edge Application Development with Just a Few Commands

AI is expanding beyond the data center as developers build a new generation of agents to act at the edge: monitoring driver attention and cabin conditions, helping robots understand their surroundings and plan tasks, and coordinating fleets of machines on production lines. These

推荐理由它能通过简单的几条命令快速在边缘端运行AI模型,用于实时监测驾驶员注意力与座舱环境状态、协助机器人理解周边环境并规划具体作业,以及在生产线上统一协调管理各类机器设备以实现协同运作。
Agent与工具NVIDIA Developer GenAI
#12

2026 年,AI 编程 Agent 的真正分水岭——Harness 详解

📌 一句话摘要 本文深入探讨了 AI 编程 Agent 的核心架构,强调了 Harness(执行框架)在决定 Agent 实际表现中的关键作用,并分析了开源社区和官方解决方案的最新进展。 📝 详细摘要 随着大模型能力的趋同,Harness 成为区分优秀与普通 Agent 的决定性因素。文章通过具体案例(如 Can Bölük 的 Hashline 实验)展示了优化编辑工具如何显著提升成功率,并介绍了 Oh-My-* 生态中各项目的创新功能。同时,分析了 Anthropic 的 Claude Managed Agents,其通过解耦 Brain、Hands

推荐理由它能用来指导构建和优化 AI 编程智能体的执行框架,通过解耦思考大脑与工具执行、改良代码编辑工具等机制,在大模型能力趋同的背景下显著提升实际编程成功率与工程表现,从而打造出真正具备代差优势的顶尖编程智能体。
Agent与工具BestBlogs.dev
#14

AI 编程导师挑战低端 Android 手机!不用服务器,Python 和 SQL 直接在浏览器里运行

推荐理由Efiwe 平台可以在没有笔记本电脑、稳定宽带和云端服务器的情况下,直接在智能手机浏览器里本地运行 Python 与 SQL 代码,并借助 AI 导师提供交互式指导,用于支持学习者仅凭一部手机就能随时随地、不受网络掉线影响地完成编程学习与代码实践。
产品接入行业观察InfoQ 中文
#25

Answer-Only Disclosure: Private-Context LLM Assistance over Web APIs with a Leakage Ledger

arXiv:2610.38126v1 Announce Type: cross Abstract: Web assistants increasingly answer questions about a user's private documents by pairing a small on-device model with a cloud LLM behind a Web API. In collaborative decoding, the document stays on the client, and the cloud receive

推荐理由Answer-Only Disclosure: Private-Context:arXiv:2610.38126v1 Announce Type: cross Abstract: Web assistants increasingly answer。
模型与评测arXiv cs.AI 官方
#26

Beyond LLM Wrappers: Context Engineering and the Three-Engine Architecture for Reliable Financial AI

arXiv:2610.39230v1 Announce Type: new Abstract: Financial AI systems must support decision-bearing questions involving payments, collections, cash flow, and compliance while ensuring numerical accuracy, traceability, and auditability. Large language models (LLMs) enable natural l

推荐理由Beyond LLM Wrappers: Context:arXiv:2610.39230v1 Announce Type: new Abstract: Financial AI systems must support。
模型与评测arXiv cs.AI 官方
#27

Beyond fabrication: Misattributed numbers in papers written by AI research agents

arXiv:2610.38691v1 Announce Type: new Abstract: Verifying numerical claims in research written by AI agents is an important but challenging problem. Recent benchmarks show that many agent-written papers fail integrity checks, but such verdicts, often produced by a single LLM judg

推荐理由Beyond fabrication: Misattributed:arXiv:2610.38691v1 Announce Type: new Abstract: Verifying numerical claims in research。
模型与评测arXiv cs.AI 官方
#28

BiShield-TEE: On the (In-)Security of Unilateral Weight Obfuscation in On-Device TEE-Shielded LLM Partition

arXiv:2610.21565v3 Announce Type: replace-cross Abstract: On-device deployment of large language models (LLMs) is increasingly adopted due to latency and privacy requirements, but exposes proprietary models to reverse engineering and intellectual property theft. Trusted Execution

推荐理由BiShield-TEE: On the (In-)Security:arXiv:2610.21565v3 Announce Type: replace-cross Abstract: On-device deployment of large。
模型与评测arXiv cs.AI 官方
#29

Can LLMs Faithfully Solve Ontology Engineering Tasks? A Mechanistic Interpretability Study

arXiv:2610.38326v1 Announce Type: new Abstract: Ontological knowledge underpins large language model (LLM) performance on knowledge-intensive tasks. However, existing evaluations of LLMs' ontological understanding largely rely on behavioral correctness, leaving the underlying mec

推荐理由Can LLMs Faithfully Solve Ontology:arXiv:2610.38326v1 Announce Type: new Abstract: Ontological knowledge underpins large。
模型与评测arXiv cs.AI 官方
#30

Comparing Human Role-Players and LLM-Simulated Clients in Online Counselling Training: An Analysis of Counselling Patterns

arXiv:2610.40563v1 Announce Type: new Abstract: This study investigates the capabilities of Large Language Models to simulate counselling clients in educational role-plays in comparison to human role-players. Initially, we recorded role-playing sessions, where novice counsellors

推荐理由Comparing Human Role-Players:arXiv:2610.40563v1 Announce Type: new Abstract: This study investigates。
模型与评测arXiv cs.AI 官方
#32

Epistemic Warrant for LLM Recommendations: Characterizing the Basis for Reliance When Ground Truth Is Unavailable

arXiv:2609.04127v2 Announce Type: replace Abstract: Large language models are increasingly used to support organizational decisions. Despite their rapid and widespread adoption, users often lack a principled basis for assessing whether to rely on a specific recommendation. We int

推荐理由Epistemic Warrant for LLM:arXiv:2609.04127v2 Announce Type: replace Abstract: Large language models are。
模型与评测arXiv cs.AI 官方
#33

HEMO: Harness Self-Evolution for Multi-Objective Combinatorial Optimization

arXiv:2610.40023v1 Announce Type: cross Abstract: Automatic operator design (AOD) has increasingly adopted large language models (LLMs) to generate problem-specific search and variation operators for multi-objective combinatorial optimization (MOCO). Yet most methods evolve the o

推荐理由HEMO: Harness Self-Evolution:arXiv:2610.40023v1 Announce Type: cross Abstract: Automatic operator design (AOD) has。
模型与评测arXiv cs.AI 官方
#15

Making it easier for websites to express AI training preferences

OpenAI will honor a shared robots.txt signal to help website operators communicate their AI training preferences to participating providers.

推荐理由这项功能允许网站管理者通过通用的 robots.txt 协议信号,直接向 OpenAI 以及其他参与支持的 AI 服务商明确传达网站内容是否可用于模型训练,从而便捷、统一地表达站点的数据训练偏好。
产品接入OpenAI News
#34

Interpretable Feature Discovery from Unstructured Data Using LLMs and Statistical Choice Models

arXiv:2610.38082v1 Announce Type: cross Abstract: Feature extraction from unstructured data typically relies on opaque embeddings unsuited to interpretable decision-making. Interpretable features, on the other hand, typically require costly, and often infeasible, hand-engineering

推荐理由Interpretable Feature Discovery from:arXiv:2610.38082v1 Announce Type: cross Abstract: Feature extraction from unstructured。
模型与评测arXiv cs.AI 官方
#35

LLM-Assisted Optimization for Simulation-Based Redesign

arXiv:2610.39275v1 Announce Type: new Abstract: Engineering design frequently involves redesigning a prior solution to adapt to changes in context, such as material prices or system requirements. Redesign often leverages simulators too complex and/or computationally intensive for

推荐理由LLM-Assisted Optimization:arXiv:2610.39275v1 Announce Type: new Abstract: Engineering design frequently involves。
模型与评测arXiv cs.AI 官方
#36

Masked Erosion: How Acceptance Gates Lose Redundant Safeguards in Self-Improving Agents

arXiv:2610.38392v1 Announce Type: new Abstract: Self-improving LLM agents edit their own harness, the prompts and rules around a fixed model, and keep an edit only if an acceptance gate scores it higher on a batch of tasks. Such a gate sees what the harness does under the current

推荐理由Masked Erosion: How Acceptance Gates:arXiv:2610.38392v1 Announce Type: new Abstract: Self-improving LLM agents edit their。
模型与评测arXiv cs.AI 官方
#37

Poisoning Agentic Alpha: Adversarial Vulnerabilities Across Roles and Architectures in Multi-Agent Trading Systems

arXiv:2608.24069v2 Announce Type: replace Abstract: LLM-based multi-agent trading systems are moving from research prototypes to live deployments that control real assets. They ingest news and social media from the open web and pass it between agents, so a single corrupted signal

推荐理由Poisoning Agentic Alpha: Adversarial:arXiv:2608.24069v2 Announce Type: replace Abstract: LLM-based multi-agent trading。
模型与评测金融arXiv cs.AI 官方
#38

SCOPE: Selective Critical-Step On-Policy Self-Distillation for Agentic Reinforcement Learning

arXiv:2610.38391v1 Announce Type: new Abstract: Outcome-based reinforcement learning provides coarse supervision for long-horizon LLM agents: failed trajectories may contain correct steps, while successful trajectories can contain errors. Trajectory-level skills can also shift te

推荐理由SCOPE: Selective Critical-Step:arXiv:2610.38391v1 Announce Type: new Abstract: Outcome-based reinforcement learning。
模型与评测arXiv cs.AI 官方
#39

The Athlete as a Scientist of One: Agentic Bayesian Experimental Design for Individualized Physiology from Consumer Wearables

arXiv:2610.40370v1 Announce Type: cross Abstract: Large language model (LLM) agents for personal health read wearable data and recommend, but do not learn about the individual in a way that can be audited or falsified. We present EpiCoach, an agentic system that treats one athlet

推荐理由个人 AI 代理 面向个人场景的代理产品。
模型与评测arXiv cs.AI 官方
#40

The Real Cost of Context: Predicting Compute Time and Energy Consumption in LLM Prefill and Decode Phases

arXiv:2610.39621v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into agentic architectures has substantially increased token consumption, raising concerns about their energy footprint. Yet, estimating the energy consumption of proprietary API-based

推荐理由The Real Cost of Context: Predicting:arXiv:2610.39621v1 Announce Type: new Abstract: The integration of Large Language。
模型与评测arXiv cs.AI 官方
#41

Towards AI-Assisted Clinical Trial Matching: Practical Considerations, Multicenter Evaluation, and Real-World Deployment

arXiv:2609.01202v2 Announce Type: replace-cross Abstract: Clinical trials are essential for evidence-based medicine and drug development, but many fail because of insufficient patient enrollment. Although there is growing interest in using AI to support patient recruitment, exist

推荐理由Towards AI-Assisted Clinical Trial:arXiv:2609.01202v2 Announce Type: replace-cross Abstract: Clinical trials are essential。
模型与评测生信医疗arXiv cs.AI 官方
#42

TrussTutor-Bench: Benchmarking large language models on solution accuracy, sycophancy, and error detection in statics

arXiv:2610.38917v1 Announce Type: cross Abstract: Large language models (LLMs) have rapidly become a default source of help for students in science and engineering courses. In foundational engineering mechanics courses such as statics, students routinely use these tools to check

推荐理由TrussTutor-Bench: Benchmarking large:arXiv:2610.38917v1 Announce Type: cross Abstract: Large language models (LLMs) have。
模型与评测教育arXiv cs.AI 官方
#43

Well-Specified and Well-Tested? Assessing SWE-bench-Style Datasets with a Self-Evolving Agent

arXiv:2610.39417v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong performance on software engineering (SE) tasks, driving the need for high-quality datasets for reliable training and evaluation. SWE-bench-style datasets (SWE datasets) are widely use

推荐理由Well-Specified and Well-Tested?:arXiv:2610.39417v1 Announce Type: cross Abstract: Large language models (LLMs) have。
模型与评测arXiv cs.AI 官方
#44

When Is Smaller Greener? Right-Sizing Language Models for Agentic AI

arXiv:2610.19345v2 Announce Type: replace Abstract: AI agents use a large language model (LLM) to plan and act over many steps. Which model should an agent use, so that its tasks are completed reliably with the least energy, cost and time? We treat this as a multi-criteria decisi

推荐理由When Is Smaller Greener? Right-Sizing:arXiv:2610.19345v2 Announce Type: replace Abstract: AI agents use a large language。
模型与评测arXiv cs.AI 官方
#45

Whom Do AI Agents Serve? Role-Induced Sponsorship Bias in Decision Models and Generative LLMs

arXiv:2609.17989v3 Announce Type: replace-cross Abstract: Consumers increasingly delegate product search to AI shopping agents powered either by generative large language models (LLMs) that deliberate in natural language or by non-generative decision models that output calibrated

推荐理由Whom Do AI Agents Serve? Role-Induced:arXiv:2609.17989v3 Announce Type: replace-cross Abstract: Consumers increasingly。
模型与评测arXiv cs.AI 官方
#16

Community safety report and new protections for teens

OpenAI is strengthening violence prevention in ChatGPT with expanded safeguards, earlier interventions, and a new commitment to public safety reporting.

推荐理由这项机制能用于在ChatGPT中更早识别并拦截暴力风险、对青少年提供更完善的安全防护与早期干预,同时通过定期的公开安全报告展现防护成效,方便公众监督与了解平台的安全治理进展。
产品接入OpenAI News
#19

@anthropic-ai/claude-code@2.1.316

Use Claude, Anthropic's AI assistant, right from your terminal. Claude can understand your codebase, edit files, run terminal commands, and handle entire workflows for you.

推荐理由它能让你直接在终端调用 Anthropic 的 AI 助手 Claude,不仅可以深度理解整个代码库与项目结构,还能自动编辑与修改文件、执行各类终端命令,并自主协助处理完整的开发工作流程。
编码代理Anthropic Watch 非官方
#20

[AINews] Building AIE CODE: The top Coding Agent Conference

It’s a quiet day, so as we have done once per conference, we’ll do a behind the scenes look at AI Engineer , now serving 6M views a month for 1.8M monthly unique viewers . CODE is the last flagship AIE of the year (there are also 2 partner conferences coming up - AIEi Shanghai ta

推荐理由你可以通过这篇内容深入了解顶尖编程智能体大会 AIE CODE 的幕后筹备过程,洞察月浏览量达600万次且拥有180万独立观众的 AI 工程师平台的运作细节,并获取该年度收官旗舰盛会及上海等合作峰会的最新动态。
编码代理Latent Space
#22

Claude Code found a root backdoor on my cheap Android TV stick, then ported mainline Linux to it over USB, with Sonnet building and Opus auditing every step before anything touched

I bought a no-name "DQ10" Android TV stick (Allwinner H618) and asked Claude Code to "reflash it with clean firmware and make it safe". About two days later: the stick runs mainline U-Boot + Armbian (kernel 6.18.53) from its own eMMC; the factory Android is completely wiped, and

推荐理由彻底清除后门并刷入主线 Armbian 后,这根廉价电视棒可以变成一台安全可靠、超低功耗的 Linux 微型服务器,直接依靠板载 eMMC 独立运行,用于搭建家庭 Docker 容器、智能家居中控网关、轻量级私有云或全天候运行的本地测试节点。
编码代理Anthropic Watch 非官方
#48

Learning and Transferring Closed-Loop Robot Software

arXiv:2609.19906v2 Announce Type: replace-cross Abstract: Closed-loop robot policies require observation processing, state management, and situation-dependent branching, making them costly to design and tune manually. Although coding agents increasingly support control-code gener

推荐理由Learning and Transferring Closed-Loop:arXiv:2609.19906v2 Announce Type: replace-cross Abstract: Closed-loop robot policies。
模型与评测arXiv cs.AI 官方
#51

A Tutorial on Generative Models for Music Audio

arXiv:2610.38252v1 Announce Type: cross Abstract: Music audio generation spans instrumental clips, full songs with vocals, edits of existing recordings, and systems that play alongside a musician in real time. This monograph explains the methods behind these systems for readers f

推荐理由A Tutorial on Generative Models:arXiv:2610.38252v1 Announce Type: cross Abstract: Music audio generation spans。
模型与评测教育arXiv cs.AI 官方
#52

Advancing Clinical Genomic Analysis with a Skill-Centred Agent

arXiv:2610.40556v1 Announce Type: new Abstract: Clinical genomic analysis requires experts to integrate evolving guidelines, databases, and computational evidence. As sequencing has become increasingly accessible, this complex and labor-intensive process has become a major bottle

推荐理由Advancing Clinical Genomic Analysis:arXiv:2610.40556v1 Announce Type: new Abstract: Clinical genomic analysis requires。
模型与评测生信医疗arXiv cs.AI 官方
#72

zaxchou/esp-mosaico-striker

基于 ESP-Mosaico(ESP32-S31 + 480×480 显示屏 + 交互子板)复刻的经典弹幕生存游戏:一条命、不能射击、只用左右移动,在越来越疯狂的字弹地狱里坚持 60 秒。

推荐理由基于 ESP-Mosaico(ESP32-S31 + 480×480 显示屏 + 交互子板)复刻的经典弹幕生存游戏:一条命、不能射击、只用左右移动,在越来越疯狂的字弹地狱里坚持 60 秒。
产品接入硬件边缘GitHub search