今日必看

Profiling TorchNeuron (Part 1): System-level profiling on AWS Trainium.

Granite Speech 5.0: Transcribe, Translate, and Attribute more Accurately and Faster

Patch the Planet: global response coordination as agents uncover vulnerabilities

ChatGPT Ads expands to 26 new countries as over 100,000 advertisers have used the platform

From local businesses to global brands, more advertisers can now reach people as they explore, compare and decide what to buy in ChatGPT.

OpenAI models are coming to Google Cloud

Large Multimodal Models for Direct Robot Control: GPT-6 as a Beginning

arXiv:2610.28259v1 Announce Type: new Abstract: Recent advances in visuospatial understanding and agentic reasoning enable direct robotic manipulation with general-purpose multimodal models, but their embodied capabilities remain poorly understood. This paper systematically evalu

Refuses When Asked, Complies When Acting: A Runtime Safety Check for Robot Control Loops

arXiv:2610.27350v1 Announce Type: cross Abstract: Frontier models can control robots through agent harnesses that loop on one question: what motion comes next toward the user's goal? We show that this default loop carries out harmful instructions. With GPT-6 Astra controlling a l

AM-Bench: A Unified Taxonomy and Evaluation Suite for Agentic Misalignment

arXiv:2610.24264v2 Announce Type: replace Abstract: As LLM-based agents are deployed with increasing autonomy in real-world environments, a critical failure mode emerges: agentic misalignment, where agents choose harmful actions over failure. However, existing safety benchmarks p

Aptamers as a sandbox for lab-in-the-loop agentic molecular discovery

arXiv:2610.24806v1 Announce Type: cross Abstract: Despite breakthroughs in AI-driven molecular generation, existing discovery pipelines operate largely in silico, with wet-lab feedback reserved for validation rather than iterative improvement. Whether large language model (LLM)-b

ClawMMU: Protection-Coherent Virtual Memory for Stateful LLM Agents

arXiv:2610.28093v1 Announce Type: cross Abstract: AI agents keep long-term memory, much of which comes from web pages and tool results. Agent harnesses, the software that runs the model, do not record who may act on this memory, so an instruction hidden in a fetched page can be t

Does Multi-Agent Collaboration Reduce Hallucination in Clinical Tasks?

arXiv:2610.27027v1 Announce Type: new Abstract: Multi-agent LLM systems improve performance on clinical tasks, and that improvement is often read as evidence of a more trustworthy system. However, the two are not the same claim. A clinician acts on the stated reasoning and not on

EGI-BENCH: An Enterprise General Intelligence Benchmark Suite

arXiv:2610.27234v1 Announce Type: new Abstract: Enterprise adoption of LLMs in agentic workflows is gated by evaluations that span a wide arc of abilities: CRM operations, heterogeneous-document retrieval, personal data understanding, multi-turn planning, tool use, function calli

Industrial Agentic AI: LLM-Driven New-Generation Agents for Smart Manufacturing

arXiv:2610.26941v1 Announce Type: new Abstract: Large language models (LLMs) are enabling agents to move beyond predefined workflows toward autonomous planning and execution, creating new opportunities for smart manufacturing. However, dynamic environments, complex physical const

Local Work, Global Progress: A Convergence Theory of AI Agent Collaboration

arXiv:2610.28286v1 Announce Type: cross Abstract: Teams of large language model (LLM) agents are increasingly applied to complex tasks, but their collaboration protocols are mostly designed empirically, without convergence guarantees. We formalize collaborative problem solving as

MAS-Guard: Unified Guardrails from Individual Agents to Multi-Agent LLM Systems

arXiv:2610.28397v1 Announce Type: cross Abstract: Agentic AI extends large language models (LLMs) from generating responses to planning and executing complex workflows, substantially expanding their utility while exposing applications to unsafe actions, information leakage, and a

MaD-RSI: Model-as-Data for Recursive Self-Improvement of Agent Harnesses

arXiv:2610.28201v1 Announce Type: new Abstract: Recursive self-improvement (RSI) of agent harnesses has emerged as an effective approach to enhancing the capabilities of large language model (LLM) agents. By searching the harness space for a specific LLM on a given dataset, RSI c

Navalia: Advancing Cowork Agents through Verifiable Task Synthesis and Long-Horizon Post-Training

arXiv:2610.26887v1 Announce Type: new Abstract: Large language model (LLM) agents are evolving from conversational assistants into Cowork Agents capable of autonomous planning, tool use, and complex task execution. Financial analysis requires these agents to integrate cross-docum

REM: What to Store, When to Recall, What to Forget in Experience Memory for Coding Agents

arXiv:2610.27377v1 Announce Type: new Abstract: Large language model (LLM) agents now autonomously complete long-horizon tasks, such as repository-level coding, through hundreds of think-act steps, yet the experience each run produces is rarely reused on the next. Prior memory sy

RITE: Evaluating End-to-End Resilience to Silent Tool Errors in E-Commerce Agentic Systems

arXiv:2610.27777v1 Announce Type: new Abstract: Tool-using LLM agents increasingly answer e-commerce queries through multi-step tool interactions. The expected output of a tool call can shift between agent development and execution, allowing a plausible but incorrect value to be

VEOcc++: Learning Persistent Voxel Feature Maps for Embodied Online Semantic Occupancy Mapping and Offline Refinement

arXiv:2610.27704v1 Announce Type: new Abstract: Semantic occupancy mapping supports embodied perception during exploration and detailed scene understanding afterward, giving rise to two complementary requirements: online incremental mapping for maintaining an up-to-date global ma

WildAIGC-Bench: Can AI Image Detectors Handle the Wild? A Benchmark of Generated and Edited Images in Online Circulation

arXiv:2610.28087v1 Announce Type: new Abstract: AI-generated images linked to news events and online claims can mislead audiences, enable fraud, or cause public controversy. We introduce WildAIGC-Bench, built through recurring collection across news websites, fact-checking source

AutoRedClaw: Automated Red-Teaming for Claw-Style Agents

arXiv:2610.27244v1 Announce Type: cross Abstract: Agent systems are shifting from task-scoped tool-use agents to persistent, personalized assistants such as OpenClaw. These claw-style agents maintain configuration files (e.g., AGENTS.md), long-term memory, and reusable skills. On

Which Depth Estimator for Jetson AGX Orin? A 2026 Benchmark of Monocular and Stereo Methods

arXiv:2610.27199v1 Announce Type: cross Abstract: The Jetson AGX Orin is a common computer for robots and vehicles, yet measured accuracy, speed and energy of current depth estimators on it are hard to find. We benchmark nine model families as of October 2026: the monocular Depth

How we built ChatGPT’s novel ad stack for user trust and relevance

Learn how OpenAI built ChatGPT’s LLM-powered ad stack to understand conversational intent, keep ads separate from answers, and deliver relevant ads at scale.