Pai 的 AI 雷达
含近几日仍热话题，按时间衰减排序。今天先看 langroid/langroid，其次 SamurAIGPT/muapi-comfyui。并行还有 GitHub Copilot app for Beginners: How to teach Copilot about your codebase、Push attribution for commits in limited public preview。
📌 一句话摘要 作者利用 Anatomy Skill 结合多种 AI 工具，制作了一段关于芯片制造过程的高质量科普视频。 📝 详细摘要 作者展示了如何利用 Anatomy Skill 将复杂的机械结构转化为等轴测动画，并结合 Grok Bot 和即梦（Jimeng）工具，成功产出一段逻辑清晰的芯片制造科普视频。 💡 主要观点 Anatomy 的风格 该 Skill 能把复杂机械结构变成风格独特的等轴立体动画。 多工具组合 作者结合 Grok bot 和即梦生成的图片与视频，做出芯片制造科普视频。 💬 文章金句 能将复杂的机械结构变成一个风格非常独特的等轴
📌 一句话摘要 介绍 GitHub 约 4.8 万 Star 的 OpenMontage：用自然语言驱动 Claude Code/Cursor 完成脚本到导出的视频流水线。 📝 详细摘要 推文介绍开源项目 OpenMontage：用户可用自然语言让 Claude Code、Cursor 等工具自动完成写脚本、找素材、配音字幕、镜头编排与导出；也可丢入参考视频分析节奏与风格并给出 2～3 个制作方向。称底层有 12 条流水线、100+ 工具与 700+ Agent Skills；展示案例中 60 秒动画短片成本约 1.23 美元。附项目链接。 💡 主要观点
arXiv:2610.13455v1 Announce Type: new Abstract: Large language models (LLMs) have taken the world by storm. Their ability to communicate with us in our own language, and to reason about our world, has made them a favorite tool for writing, answering questions, and much more. Thei
arXiv:2610.13600v1 Announce Type: cross Abstract: Large Audio Language Models (LALMs) achieve strong performance on speech-text tasks, but standard audio encoders produce hundreds of tokens for even short audio clips. Because self-attention scales quadratically in sequence length
arXiv:2610.13116v1 Announce Type: new Abstract: As large language models (LLMs) acquire advanced biological design capabilities, they offer substantial research benefits but simultaneously introduce severe dual-use risks, such as engineering enhanced pathogens or drug-resistant b
arXiv:2610.12762v1 Announce Type: new Abstract: Hardware datasheets contain engineering specifications essential for component selection, system integration, and hardware compatibility verification. However, manual inspection is tedious and error-prone because datasheets are leng
arXiv:2610.13015v1 Announce Type: cross Abstract: Reinforcement learning has become the foundational paradigm for enhancing the reasoning capabilities of LLMs. Yet the dominant approach, Proximal Policy Optimization (PPO), relies on a geometrically degenerate clipping proxy that
arXiv:2610.13494v1 Announce Type: new Abstract: Existing LLM-based agent approaches for long-horizon machine learning engineering (MLE) often use context engineering, implemented through custom harnesses that manage tools, skills, and accumulated experience. However, we find that
arXiv:2610.13632v1 Announce Type: new Abstract: Large language model (LLM) agents are rapidly improving on long-horizon scientific and olympiad tasks. Recent systems have produced a Lean-formalized resolution of the Navier--Stokes problem and autonomous solutions to four open que
arXiv:2607.22724v2 Announce Type: replace-cross Abstract: Group-based policy optimization has been increasingly used to train large language model (LLM) agents from sparse outcome rewards by comparing trajectories or steps within a group. However, on difficult long-horizon agenti
arXiv:2607.04528v2 Announce Type: replace Abstract: Software agents are becoming increasingly important in modern coding workflows, where they solve complex tasks through multi-step interaction with code repositories. A central component of these systems is the execution harness,
arXiv:2610.13438v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a key paradigm for improving large language model (LLM) agents, enabling stronger reasoning, planning, and tool-use in interactive environments. However, existing agent RL methods remain fu
arXiv:2610.13145v1 Announce Type: new Abstract: Large language models (LLMs) increasingly generate structured layouts and executable scene programs from natural-language instructions. However, executability does not imply engineering feasibility: an industrial scene program may e
arXiv:2610.13416v1 Announce Type: new Abstract: Large language model (LLM) agents are becoming direct users of the open web. As they take on increasingly complex and information-intensive tasks, effective web access is becoming a core capability for agentic problem solving. Exist
arXiv:2608.06202v2 Announce Type: replace-cross Abstract: Large language model (LLM) benchmark evaluations are routinely used to support claims about model safety, reliability, and deployment readiness. Yet most evaluations rely on a single access modality (model APIs), perform a
arXiv:2610.13092v1 Announce Type: new Abstract: AI agents depend on repeated decisions to accomplish tasks, with large language models (LLMs) commonly serving as their core decision makers. The recent emergence of Jev offers an opportunity to make these decisions faster and at lo
arXiv:2607.09996v2 Announce Type: replace Abstract: Automated failure attribution uses LLMs to identify where and why agentic systems fail. As agents become more capable, their failures become subtler, making automated attribution increasingly important. We introduce Who&When Pro
arXiv:2610.13692v1 Announce Type: cross Abstract: Standard Policy Gradient (PG) algorithms suffer from high estimation variance because they rely on Monte Carlo updates. While off-policy variance reduction mitigates this problem, establishing optimal sample complexity currently r
arXiv:2609.37686v2 Announce Type: replace Abstract: Autonomous agents have made rapid progress in general-purpose computer use, yet reliable automation of professional industrial engineering remains out of reach. Engineering workflows require reasoning over geometric and physical
arXiv:2610.13572v1 Announce Type: new Abstract: Humanoid tennis requires reactive whole-body coordination under rapidly changing ball dynamics, yet collecting task-specific motion-capture demonstrations that cover diverse approach states, contact locations, and timing conditions
arXiv:2610.12780v1 Announce Type: new Abstract: This paper presents the computational architecture and quantitative preclinical evaluation of MIRAGE, a multimodal image-guided robotic surgery framework for real-time visualization and navigation. It integrates stereovision scene r
arXiv:2609.39304v2 Announce Type: replace-cross Abstract: When an off-the-shelf coding agent is used directly as a robot policy, observing a browser-based 3D interface through screenshots and acting by posing a virtual target gripper through a few tools, the agent's harness, its
arXiv:2610.13079v1 Announce Type: new Abstract: Third-person human videos offer a scalable alternative to task-specific reward engineering, teleoperation, and manually scripted demonstrations for humanoid loco-manipulation. Recent video-to-humanoid systems have shown that noisy h
📌 一句话摘要 作者幽默地提议开发一种将握力与 AI 推理强度关联的健身硬件，让用户在等待 AI 计算时进行锻炼。 📝 详细摘要 作者提出了一种有趣的硬件构想：开发一套类似于 Codex 或 Claude Code 的配套健身硬件。通过将 AI 的推理强度与用户的握力大小挂钩，激励用户在等待 AI 思考（Thinking）的间隙通过练习握力训练来提升性能。 💡 主要观点 跨界联动创意 将 AI 的计算资源（推理强度）与人类的身体活动（握力）进行逻辑关联。 解决 AI 等焦虑 利用当前大模型在复杂推理时产生的等待空档，将碎片化时间转化为健身时间。 💬 文章