Pai 的 AI 雷达

今日必看

含近几日仍热话题,按时间衰减排序。今天先看 Tavris1/ComfyUI-Easy-Install,其次 steel-dev/steel-browser。并行还有 GitHub Security Lab 发布 LLM 驱动的 Fuzzing Taskflow,自动完成 C/C++ 项目模糊测试全流程、Require proof of presence for high-impact actions。

日期
2026/09/25
今日条目
93

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#33

AgenticSizing: A Large Language Model-based Multi-Agent Framework for Analog Circuit Sizing

arXiv:2609.25873v1 Announce Type: new Abstract: Analog circuit sizing remains a challenging and time-consuming task due to the large design space, strong performance trade-offs, and increasing circuit complexity in scaled technologies. Although recent large language model (LLM)-b

推荐理由AgenticSizing: A Large Language:arXiv:2609.25873v1 Announce Type: new Abstract: Analog circuit sizing remains。
模型与评测arXiv cs.AI 官方
#34

CQ4OE: A benchmark for assessing LLM-assisted ontology generation from competency questions

arXiv:2609.26029v1 Announce Type: new Abstract: Ontology generation from Competency Questions (CQs) is a central yet labor-intensive phase of Ontology Engineering. While large language models (LLMs) offer promising automation capabilities, current evaluations remain fragmented. T

推荐理由CQ4OE: A benchmark for assessing:arXiv:2609.26029v1 Announce Type: new Abstract: Ontology generation from Competency。
模型与评测arXiv cs.AI 官方
#35

From Experts to Sub-experts: Fine-grained Parameter-Efficient Fine-Tuning for MoE LLMs

arXiv:2609.25655v1 Announce Type: cross Abstract: As large language models (LLMs) scale rapidly, dense full-parameter adaptation becomes increasingly expensive, motivating sparse and modular architectures such as Mixture-of-Experts (MoE) models. This shift raises a key question f

推荐理由From Experts to Sub-experts:arXiv:2609.25655v1 Announce Type: cross Abstract: As large language models (LLMs) scale。
模型与评测arXiv cs.AI 官方
#36

Grow the Harness, Not the Context: From Strategy-Free Scaffolds to Reusable Specialist Agents

arXiv:2609.26760v1 Announce Type: new Abstract: Large language model (LLM) agents often handle streams of related tasks, yet standard harnesses repeatedly ask the model to reconstruct the same control decisions inside each task's context. We study whether task feedback can instea

推荐理由Grow the Harness, Not the Context: From:arXiv:2609.26760v1 Announce Type: new Abstract: Large language model (LLM) agents often。
模型与评测arXiv cs.AI 官方
#37

Passes Alone, Fails Together: Benchmarking Semantic Coordination in Parallel LLM-Agent Development

arXiv:2609.25396v1 Announce Type: cross Abstract: Parallel coding agents can produce patches that work alone but fail when merged. This happens when one agent changes an interface or rule that another agent still relies on. We study these failures with stale, a benchmark for sema

推荐理由Passes Alone, Fails Together:arXiv:2609.25396v1 Announce Type: cross Abstract: Parallel coding agents can produce。
模型与评测arXiv cs.AI 官方
#38

Quantifying Overclaiming Propensity in Frontier LLM Agents

arXiv:2609.20812v3 Announce Type: replace-cross Abstract: Frontier coding agents are increasingly trusted to work autonomously for long periods of time, yet what they actually did is often hard to tell from their final response. We quantify the propensity of such agents to overcl

推荐理由Quantifying Overclaiming Propensity:arXiv:2609.20812v3 Announce Type: replace-cross Abstract: Frontier coding agents are。
模型与评测arXiv cs.AI 官方
#39

Qwen-Audio-3.1-Realtime: Towards Reliable Agentic Voice Interaction

arXiv:2609.25176v1 Announce Type: cross Abstract: Real-time voice assistants must reason over evolving requests, execute actions, and follow conversational rules. Qwen-Audio-3.1-Realtime brings these requirements together through Think, Act, and Speak and Coordinate. Think combin

推荐理由Qwen-Audio-3.1-Realtime: Towards:arXiv:2609.25176v1 Announce Type: cross Abstract: Real-time voice assistants must。
模型与评测arXiv cs.AI 官方
#40

ReasonLab: A Controlled and Auditable Evaluation of Prompting Techniques for Multiple-Choice QA

arXiv:2607.14109v2 Announce Type: replace-cross Abstract: Probing the capabilities of Large Language Models (LLMs) and building robust solutions for Multiple-Choice Question Answering (MCQA) remain central challenges in natural language understanding. Furthermore, the rapid proli

推荐理由ReasonLab: A Controlled and Auditable:arXiv:2607.14109v2 Announce Type: replace-cross Abstract: Probing the capabilities。
模型与评测arXiv cs.AI 官方
#41

Recovering Agentic Sovereignty: Mitigating the Consensus Paradox via Contrastive Epistemic Decoding

arXiv:2609.25570v1 Announce Type: new Abstract: Large language models (LLMs) exhibit a parametric vulnerability to adversarial swarm consensus. To mitigate this sycophancy, we introduce Contrastive Epistemic Decoding (CED), a zero-shot inference intervention. Unlike standard Cont

推荐理由Recovering Agentic Sovereignty:arXiv:2609.25570v1 Announce Type: new Abstract: Large language models (LLMs) exhibit。
模型与评测arXiv cs.AI 官方
#42

Reducing Hallucinations in Large Language Models Through Integrated Self-Verification and Retrieval-Augmented Generation

arXiv:2609.26229v1 Announce Type: cross Abstract: Large Language Models (LLMs) are progressively used for advanced engineering tasks, includes Computer-Aided Design (CAD) documentation, standards compliance verification, and knowledge retrieval. Still, they are prone to produce h

推荐理由Reducing Hallucinations in Large:arXiv:2609.26229v1 Announce Type: cross Abstract: Large Language Models (LLMs) are。
模型与评测arXiv cs.AI 官方
#43

Simulate to Generalize: Scaling Stateful Supervision for API-calling Agents using LLM World Models

arXiv:2607.16900v3 Announce Type: replace Abstract: Training agents that generalize to unseen, stateful environments requires a massive dataset of state-changing trajectories covering a vast and diverse set of APIs. However, scaling this broad supervision is severely bottlenecked

推荐理由Simulate to Generalize: Scaling:arXiv:2607.16900v3 Announce Type: replace Abstract: Training agents that generalize。
模型与评测arXiv cs.AI 官方
#44

Spectra: A Rules-Driven LLM Pipeline for Automated KYC Document Processing

arXiv:2609.25474v1 Announce Type: new Abstract: Know Your Client (KYC) onboarding in capital markets requires analysts to manually classify documents, extract structured data from heterogeneous sources, and validate compliance against complex regulatory policies. This process req

推荐理由Spectra: A Rules-Driven LLM Pipeline:arXiv:2609.25474v1 Announce Type: new Abstract: Know Your Client (KYC) onboarding。
模型与评测arXiv cs.AI 官方
#45

TREND-10K: A Comprehensive Dataset for Next-Generation Video Quality Assessment Based on Preference-Driven Media

arXiv:2609.26187v1 Announce Type: new Abstract: The increasing prominence of short-video platforms, coupled with the advanced commercialization of AI-generated content (AIGC) videos, has led to a shift in the types of video media trend consumed by users in their daily lives. Trad

推荐理由TREND-10K: A Comprehensive Dataset:arXiv:2609.26187v1 Announce Type: new Abstract: The increasing prominence。
模型与评测arXiv cs.AI 官方
#46

More ways to request and configure Copilot code reviews

GitHub Copilot code review now offers additional personal configurations to an expanded set of Copilot plans and an enterprise-level default setting. These improvements are now generally available: A dedicated personal settings page for automatic review and your default review ef

推荐理由More ways to request and configure:GitHub Copilot code review now offers additional personal configurations to an expanded。
开发与开源GitHub Changelog
#47

Node 20 is no longer available in GitHub Actions

This is the final notification that Node 20 is no longer available on GitHub Actions runners. Runners now use Node 24 for JavaScript actions. The temporary ACTIONS_ALLOW_USE_UNSECURE_NODE_VERSION opt-out is no longer available. If you maintain a JavaScript action, update its runs

推荐理由Node 20 is no longer available:This is the final notification that Node 20 is no longer available on GitHub Actions。
产品接入GitHub Changelog
#49

谷歌 Gemini 3.8 Live 上线'数字人'实时对话,支持多国语言与口型同步

📌 一句话摘要 谷歌推出 Gemini 3.8 Live 功能,通过多模态实时对话技术实现多国语言口型同步,并提供企业级数字人交互方案。 📝 详细摘要 谷歌发布了 Gemini 3.8 Live,该功能支持“数字人”实时语音交互,核心亮点在于多国语言的流畅切换与口型同步技术。目前,Cox Automotive、Equal AI 和 Salesforce 等企业已接入该技术,将其应用于汽车电商、客服及 CRM 等场景。为了应对深度伪造风险,谷歌引入了 SynthID 水印技术并实施了严格的企业级身份校验与白名单机制,以确保 AI 生成内容的合规与安全。 💡

推荐理由📌 一句话摘要 谷歌推出 Gemini 3.8 Live 功能,通过多模态实时对话技术实现多国语言口型同步,并提供企业级数字人交互方案。
创作成片法律合规BestBlogs.dev
#50

AgriGen: Large-Scale Scene Generation Framework for Photorealistic Agricultural Robotics Simulation

arXiv:2609.25725v1 Announce Type: new Abstract: Agricultural robotics is advancing rapidly, yet progress remains constrained by limited field access, lack of control over field conditions, geographic variability, and seasonal crop cycles. These factors make it difficult and costl

推荐理由AgriGen: Large-Scale Scene Generation:arXiv:2609.25725v1 Announce Type: new Abstract: Agricultural robotics is advancing。
模型与评测arXiv cs.RO 官方
#51

Design and Implementation of an Ultra-Low-Cost Wall-Climbing Robot for Infrastructure Crack Detection

arXiv:2609.26130v1 Announce Type: new Abstract: Crack detection is a crucial process to ensure the safety and longevity of buildings and other infrastructure. In this paper, we developed a low-cost, automated crack detection robot that leverages CNN, EfficientNet-B0, and YOLOv8 f

推荐理由Design and Implementation of:arXiv:2609.26130v1 Announce Type: new Abstract: Crack detection is a crucial process。
模型与评测arXiv cs.RO 官方
#52

Imperfection for Precision: Upcycling Imperfect Data for High-Precision Robotic Manipulation

arXiv:2609.26672v1 Announce Type: new Abstract: Training vision-language-action (VLA) models for high-precision manipulation typically requires task-specific, high-quality data (e.g., teleoperation), which is slow and expensive to collect. To reduce this burden without compromisi

推荐理由Imperfection for Precision: Upcycling:arXiv:2609.26672v1 Announce Type: new Abstract: Training vision-language-action (VLA)。
模型与评测arXiv cs.RO 官方
#53

Toward User-Mediated Self-Repair in Ubiquitous Robots Through Goal-Oriented Agentic AI

arXiv:2609.26157v1 Announce Type: new Abstract: Ubiquitous robotic systems often lack traditional visual interfaces, necessitating resilient natural language interaction for maintenance and repair tasks. This paper presents a goal oriented agentic AI architecture designed to enab

推荐理由Toward User-Mediated Self-Repair:arXiv:2609.26157v1 Announce Type: new Abstract: Ubiquitous robotic systems often lack。
模型与评测arXiv cs.AI 官方
#54

Rendering huge pull requests in the GitHub Copilot app

Broad refactors and migrations often have to land as one change. Stacked pull requests are a great way to split work into smaller changes, which makes reviews easier and helps teams ship with less risk. But some changes, like this one, can’t be split cleanly. That leaves you with

推荐理由Rendering huge pull requests in:Broad refactors and migrations often have to land as one change。
开发与开源GitHub Changelog AI
#55

A Hybrid AI Framework for Academic Advising: Integrating Ensemble-Based Grade Prediction and a Rule-Based Expert System

arXiv:2609.26243v1 Announce Type: new Abstract: The rapidly increasing student population has posed serious challenges to the traditional academic advising process. This study designs and implements a multi-purpose intelligent system to support students' academic progress, based

推荐理由A Hybrid AI Framework for Academic:arXiv:2609.26243v1 Announce Type: new Abstract: The rapidly increasing student。
模型与评测arXiv cs.AI 官方