Pai 的 AI 雷达

今日必看

今天这份简报把编码代理的成本追踪、Claude Code 实践、Copilot 自动选模和代理编码对 CI 的影响放在前面,也收录 MoE 训练、AI 助理、代理评测、开发者活动与一批开源工具;阅读时先抓每条的事实动作,再按自己的开发、训练或产品场景筛选可复用的机制。

日期
2026/09/15
今日条目
74

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#26

Scaling Clinical Judgment to Evaluate Medical AI

arXiv:2609.12822v1 Announce Type: new Abstract: Blinded physician evaluation has been considered by many to be the gold standard for assessing clinical reasoning in large language models (LLMs). This is difficult to scale; thus, prior studies typically rely on small physician pan

推荐理由Scaling Clinical Judgment to Evaluate:arXiv:2609.12822v1 Announce Type: new Abstract: Blinded physician evaluation has been。
模型与评测生信医疗arXiv cs.AI 官方
#27

Separating Engineering Reasoning from DEXPI Serialization in LLM-Based Greenfield Surface-Process Design: A Three-Case Study for Underground Gas Storage

arXiv:2609.12656v1 Announce Type: cross Abstract: Large language models can produce engineering descriptions and structured process representations, but standards-level serialization can substantially increase the generation burden. This diagnostic study examines whether separati

推荐理由Separating Engineering Reasoning from:arXiv:2609.12656v1 Announce Type: cross Abstract: Large language models can produce。
模型与评测arXiv cs.AI 官方
#28

SoK: Rethinking Jailbreaking in the Era of Agentic AI: Attacks, Defenses, and Practical Consideration

arXiv:2609.12413v1 Announce Type: new Abstract: Large language models (LLMs) are rapidly evolving from conversational assistants into agentic AI systems that reason, plan, invoke tools, maintain persistent memory, communicate with other agents, and execute multi-step tasks. At th

推荐理由SoK: Rethinking Jailbreaking in the Era:arXiv:2609.12413v1 Announce Type: new Abstract: Large language models (LLMs) are。
模型与评测安全治理arXiv cs.AI 官方
#29

What Drives Recovery in Agentic Text-to-Cypher? LAST-CQ: An LLM Agent Self-Refinement Framework

arXiv:2609.12746v1 Announce Type: new Abstract: Agentic pipelines for structured-query generation are rapidly expanding, but it is unclear which part of the loop produces the gain. We use LAST-CQ -- a five-agent, training-free, execution-grounded Text-to-Cypher framework -- as an

推荐理由What Drives Recovery in Agentic:arXiv:2609.12746v1 Announce Type: new Abstract: Agentic pipelines for structured-query。
模型与评测arXiv cs.AI 官方
#30

When Rubrics Fail: Hallucinations Reveal Blind Spots in Medical AI Evaluation

arXiv:2609.12718v1 Announce Type: new Abstract: Hallucinations can undermine clinician trust in LLMs, making it important that evaluation methods capture clinically relevant errors. Rubric-based evaluation has become the leading approach for assessing LLMs in medicine, but it is

推荐理由When Rubrics Fail: Hallucinations:arXiv:2609.12718v1 Announce Type: new Abstract: Hallucinations can undermine clinician。
模型与评测生信医疗arXiv cs.AI 官方
#31

An Automated Thickness Evaluation Procedure Using an Integrated Structured Light 3D Camera in a Robotic Bioprinting Framework

arXiv:2609.12206v1 Announce Type: new Abstract: Bioprinting is emerging as a tissue engineering technique to replace common treatment methods for large scale injuries. While thickness of the BioPrinted Constructs (BPCs) have shown to be of importance in the cell maturation and in

推荐理由An Automated Thickness Evaluation:arXiv:2609.12206v1 Announce Type: new Abstract: Bioprinting is emerging as a tissue。
模型与评测arXiv cs.RO 官方
#32

A Multimodal Explainable Deep Learning Framework for Alzheimer's Disease Diagnosis using 3D Magnetic Resonance Imaging and Clinical Data

arXiv:2609.12410v1 Announce Type: new Abstract: Dementia is a major and growing global health burden, with Alzheimer's disease (AD) accounting for most cases. Timely and accurate diagnosis is central to managing this burden and increasingly depends on integrating complementary cl

推荐理由A Multimodal Explainable Deep Learning:arXiv:2609.12410v1 Announce Type: new Abstract: Dementia is a major and growing global。
模型与评测生信医疗arXiv cs.CV 官方
#33

Agentic TCAD Calibration Workflow for Oxide Semiconductor Transistors

arXiv:2609.12184v1 Announce Type: cross Abstract: Experimental TCAD calibration is essential for predictive technology modeling of emerging oxide semiconductor transistors. However, it remains time-consuming and expert dependent because of model ambiguity. Multiple physical model

推荐理由Agentic TCAD Calibration Workflow:arXiv:2609.12184v1 Announce Type: cross Abstract: Experimental TCAD calibration is。
模型与评测arXiv cs.AI 官方
#34

Anchoring Clinical Events in Time: UID-Preserving Multimodal Reconstruction and Source-Grounded Adjudication

arXiv:2609.13062v1 Announce Type: new Abstract: Clinical timelines support treatment-window analysis and leakage-free modeling, but discharge summaries often obscure chronology and structured EHR tables describe only part of the patient course. We present a UID-preserving framewo

推荐理由Anchoring Clinical Events in Time:arXiv:2609.13062v1 Announce Type: new Abstract: Clinical timelines support。
模型与评测生信医疗arXiv cs.AI 官方
#35

AquaCubeAI-Powered Monitoring Turbidity on-board {\Phi}sat-2

arXiv:2609.12744v1 Announce Type: new Abstract: Timely monitoring of coastal water quality is critical for environmental protection, yet conventional satellite workflows rely on downlink and ground processing, introducing latency that can limit responsiveness to rapidly evolving

推荐理由AquaCubeAI-Powered Monitoring Turbidity:arXiv:2609.12744v1 Announce Type: new Abstract: Timely monitoring of coastal water。
模型与评测arXiv cs.CV 官方
#36

Assessment of Non-Institutional AI Tool Usage Among Clinicians

arXiv:2609.11990v1 Announce Type: cross Abstract: Generative artificial intelligence (AI) tools are increasingly accessible and have the potential to improve efficiency across clinical workflows. However, clinicians may also use non-institutional AI tools that are not provided, m

推荐理由Assessment of Non-Institutional AI Tool:arXiv:2609.11990v1 Announce Type: cross Abstract: Generative artificial intelligence。
模型与评测生信医疗arXiv cs.AI 官方
#37

Automated Detection and Structuring of Social Tipping Point Evidence in Climate related Documents: A Modular AI Framework

arXiv:2609.12254v1 Announce Type: cross Abstract: The climate literature has grown faster than review teams can read it. That gap matters most for a concept like the environmental social tipping point, the threshold at which a small change triggers rapid, self-reinforcing change

推荐理由Automated Detection and Structuring:arXiv:2609.12254v1 Announce Type: cross Abstract: The climate literature has grown。
模型与评测arXiv cs.AI 官方
#38

Beyond Accuracy: Uncertainty-Guided Boundary Refinement for Reliable Biomedical Image Segmentation

arXiv:2609.12892v1 Announce Type: new Abstract: Accurate biomedical image segmentation requires not only high global overlap but also reliable delineation of clinically meaningful boundaries. In blood-smear microscopy, cytoplasm and nucleus contours provide the structural basis f

推荐理由Beyond Accuracy: Uncertainty-Guided:arXiv:2609.12892v1 Announce Type: new Abstract: Accurate biomedical image segmentation。
模型与评测生信医疗arXiv cs.CV 官方
#39

Beyond Generation and Accuracy: Diagnosing and Enhancing Visual Chain-of-Thought for Geometry Problem Solving

arXiv:2609.12606v1 Announce Type: new Abstract: While multimodal reasoning has advanced rapidly, solving complex geometry problems critically hinges on active visual assistance, such as constructing auxiliary lines, spurring the rise of Visual Chain-of-Thought (VCoT). However, ex

推荐理由Beyond Generation and Accuracy:arXiv:2609.12606v1 Announce Type: new Abstract: While multimodal reasoning has advanced。
模型与评测arXiv cs.AI 官方
#40

Bridging Vision Foundation Model Priors with CLIP for Spatial-aware Few-shot Anomaly Detection in Medical Images

arXiv:2609.12454v1 Announce Type: cross Abstract: Vision-Language Models such as CLIP enable effective few-shot medical anomaly detection (AD) via strong image-text semantic alignment. However, their globally contrastive pretraining lacks explicit spatial supervision, limiting pr

推荐理由Bridging Vision Foundation Model Priors:arXiv:2609.12454v1 Announce Type: cross Abstract: Vision-Language Models such as CLIP。
模型与评测安全治理arXiv cs.AI 官方
#41

Computing at Sea: Floating and Offshore Data Centres as a Pathway to Sustainable AI Infrastructure

arXiv:2609.12511v1 Announce Type: cross Abstract: The rapid expansion of artificial intelligence is transforming data centres into one of the world's fastest-growing sources of electricity demand. As AI systems scale in size and capability, the physical infrastructure supporting

推荐理由Computing at Sea: Floating and Offshore:arXiv:2609.12511v1 Announce Type: cross Abstract: The rapid expansion of artificial。
模型与评测arXiv cs.AI 官方
#42

CoralscapesV2: Panoptic and Fine-Grained Visual Scene Understanding in Coral Reefs

arXiv:2609.12826v1 Announce Type: new Abstract: In order to design conservation and restoration strategies to counter the global decline of coral reefs, ecological monitoring of reefs needs to be scaled up dramatically. Computer vision methods are increasingly used to tackle the

推荐理由CoralscapesV2: Panoptic:arXiv:2609.12826v1 Announce Type: new Abstract: In order to design conservation。
模型与评测arXiv cs.CV 官方
#45

3dviz‑pro‑max:三维可视化 Agent 技能

📌 一句话摘要 3dviz‑pro‑max 让 Agent 能在 Three.js 中根据配方快速构造可交互 3D 场景,并通过截图脚本实时调优渲染。 📝 详细摘要 3dviz‑pro‑max 是一个 Agent Skill,可让 Claude Code 或 Codex 在 Three.js 里根据预设配方快速搭建可交互的 3D 场景,并自带截图脚本调优。 💡 主要观点 全栈 Agent 能根据 223 条配方和 22 套组件模板自动生成 3D 视觉内容,减少手工设定。 利用已有的配方、素材和组件,Agent 可以在不到几分钟的时间内完成场景搭建与渲染。

推荐理由📌 一句话摘要 3dviz‑pro‑max 让 Agent 能在 Three。
编码代理BestBlogs.dev
#47

老卫第三个口播视频:去大公司还是小公司

📌 一句话摘要 作者发布第三个口播视频,主题是去大公司还是小公司,并认为这很多时候并非一个选择题。 📝 详细摘要 作者宣布其第三个口播视频上线,主题为「去大公司还是去小公司」,并给出核心观点:很多时候这并非一个选择题。推文本身只做预告与观点点题,未展开论证。 💡 主要观点 大公司还是小公司,很多时候不是可自由选择的题 作者以「并非选择题」点出该议题的隐含前提:机会、阶段与个人条件往往先于偏好决定结果,但推文未给出具体论证,需看视频内容。 💬 文章金句 去大公司还是去小公司?很多时候这并非一个选择题 📊 文章信息 AI 初评: 74 来源: 卫斯理(@im

推荐理由📌 一句话摘要 作者发布第三个口播视频,主题是去大公司还是小公司,并认为这很多时候并非一个选择题。
创作成片BestBlogs.dev
#48

电子书解析器开源地址

📌 一句话摘要 作者分享了基于 Foliate.js 的电子书解析器的开源项目 Github 地址。 📝 详细摘要 本推文作为前一条技术复盘的推文附件,提供了其基于 Foliate.js 实现的电子书解析器的具体 Github 开源仓库地址。 📊 文章信息 AI 初评: 60 来源: 向阳乔木(@vista8) 作者: 向阳乔木 分类: 软件编程 语言: 中文 阅读时间: 1 分钟 字数: 34 标签: 编程与工程 , 前端与 Web , 开源项目 , Microsoft , GitHub 阅读推文

推荐理由📌 一句话摘要 作者分享了基于 Foliate。
创作成片BestBlogs.dev