Search: “agents”

“The field of artificial life is a very long-term bet on intelligence.” 🐙 Our former intern Akarsh Kumar recently joined @MLStreetTalk to discuss the intersection of evolution and automated search for

arXiv:2610.11577v1 Announce Type: cross Abstract: Autonomous vehicles often suffer from limited perception due to occlusions, blind spots, limited sensor range, and the complex nature of surrounding e

arXiv:2610.11959v1 Announce Type: new Abstract: Reinforcement learning (RL) is the central training paradigm for advancing large foundation models towards self-improvement. This report introduces the

arXiv:2507.18074v2 Announce Type: replace Abstract: Recent progress in LLM agents has advanced the prospect of autonomous research. Yet whether AI can complete difficult long-horizon tasks, especially

arXiv:2610.11123v1 Announce Type: new Abstract: Most human-agent interaction today remains text-based. Natural language can impose cognitive overload, ambiguity, information chaos, and slow input for

Industrial AI is entering a new phase. After decades of predictive analytics and other specialized applications, advances in foundation models, physical AI, and agentic AI are making it possible to au

My Decoder guest today is Hayden Field, The Verge’s senior AI reporter, and we’re discussing the new wave of consumer-friendly AI agents. If you’ve been paying attention to this space, you know AI ent

arXiv:2610.10133v1 Announce Type: new Abstract: Real-world low-quality images suffer from complex mixed degradations, including but not limited to noise, blur, atmospheric effects, etc. Recent agentic

The ASUS blog post (Oct 8 2026) announces a collaboration between ASUS, Hermes, and Nous Research to launch an accessible local‑first AI chatbot aimed at creative workflows. Designed for ProArt device

arXiv:2610.10281v1 Announce Type: new Abstract: A task abstraction can specify the intended events while its spatial layout prevents a fixed agent and controller from completing them. Starting from a

Anniek Bao / CNBC: Manus' parent Butterfly Effect says it raised 500M+, led by Boyu Capital and IDG Capital, in its first funding since Meta was forced to unwind its Manus buyout — AI agent startup Ma

arXiv:2610.10310v1 Announce Type: new Abstract: Recursive self-improvement requires carrying accepted changes into later improvement cycles, while studying agent-proposed changes also requires substan

arXiv:2610.10183v1 Announce Type: new Abstract: Long video understanding increasingly relies on external memory to organize massive visual streams into compact representations. However, most memory-ba

Btw, we're hiring. We're hiring the best engineers in the world. You're ambitious. Want to make something different. You learn and build fast. Our company is growing fast, so you need to grow even fas

arXiv:2610.07751v1 Announce Type: new Abstract: Real-world reasoning rarely reduces to static question answering: agents must actively gather information from tools and sensors that are often noisy an

I’m hitting rate limits on Together AI. For context, I’ve been working on an agentic repository indexing and benchmark generation tool, and I’m running multiple agents in parallel across models like L

arXiv:2610.08142v1 Announce Type: new Abstract: Zero-shot coordination in embodied settings requires acting while the partner is intermittently out of view, leaving existing methods with ambiguous par

arXiv:2610.07645v1 Announce Type: cross Abstract: Self-improving LLM agents increasingly distill successful experiences into persistent, reusable skills. Existing skill attack methods corrupt this lea

Add a voice travel concierge to an airline app with Amazon Bedrock AgentCore, Amazon Nova Sonic for real-time speech, and Amazon Bedrock Knowledge Bases for policy answers. Travelers change seats, che

Claude Opus 5.5 leads at 63.31 and 4.99 per task. GPT 6 Astra is second at 56.25 and 11.61. Sonnet 5.5 follows at 53.14 and 2.82. At the other end, DeepSeek V4.1 Flash scores 36.91 at 0.26 and Ling 3.

arXiv:2511.07312v2 Announce Type: replace Abstract: Real-world decision-making generally involves hidden information, that is, information that is unknown to one agent but possessed by another. Unfort

arXiv:2603.19617v2 Announce Type: replace Abstract: Federated learning (FL) is a communication-efficient framework for solving distributed optimization problems. Standard FL methods aggregate local up

I tried both these models on a few small agentic tasks with tools (i.e. 'What's the weather like today?', etc.). They're both pretty solid at using web search to find answers despite being small model

The real reason why Anthropic is so DESPERATE for the Pope to recognize Ai as conscious is because if Ai just a “TOOL” then Anthropic will he LEGALLY “LIABLE” for everything the tool does.🚨👀 Because i

arXiv:2610.00238v1 Announce Type: cross Abstract: Long-term memory agents increasingly rely on it- erative search and reusable experience to answer questions over large personal, factual, or narrative

arXiv:2610.00727v1 Announce Type: cross Abstract: Controlling an agent with vision requires being able to separate useful information from irrelevant background information. JEPA-style latent world mo

Local AI is becoming more useful by the token. As AI agents move from experiments into everyday development, increasingly capable open models are shrinking to fit on more devices, giving builders more

arXiv:2602.13691v2 Announce Type: replace Abstract: Recent advancements in Large Language Model (LLM) agents have demonstrated strong capabilities in executing complex tasks through tool use. However,

arXiv:2610.01799v1 Announce Type: new Abstract: Skill evolution offers a promising way to improve large language model agents without updating their parameters, but its use in formal theorem proving r

The Adjudicated Query pattern pairs the Amazon Quick chat agent with a bounded MCP server over a deterministic rules engine to deliver provably complete, defensible compliance answers. This post walks

Agentic artificial intelligence-powered hardware systems design platform Flow Engineering Inc. announced Wednesday it has raised 50 million in early-stage funding to change how engineers develop and i

We are introducing Clef and Clef-flash, open-source decision models hosted on Workers AI for high-speed classification and agentic workflows. Also launching: a new reinforcement learning platform that

arXiv:2609.40358v1 Announce Type: new Abstract: Video world models are expected to predict how the physical world evolves, yet they often produce visually plausible videos that violate basic physical

arXiv:2609.35561v2 Announce Type: replace Abstract: Recursive self-improvement (RSI) seeks to enable AI systems to participate in improving their own capabilities. A concrete pathway is autonomous mod

arXiv:2609.38606v1 Announce Type: cross Abstract: As vibe coding becomes increasingly capable and widespread, security vulnerabilities in even functionally correct solutions are a growing concern. Whe

arXiv:2601.12310v2 Announce Type: replace Abstract: Self-training systems often degenerate due to the lack of an external criterion for judging data quality, leading to reward hacking and semantic dri

The browser has changed significantly. Rather than just a window to the web, it serves as an AI workspace and central operating environment for the modern enterprise. With knowledge workers spending o

arXiv:2609.39195v1 Announce Type: new Abstract: Spatial intelligence requires maintaining a coherent understanding of the world as the embodied agent moves. Like humans, the agent must use its own mot

Our agent workflow is currently executing a group of 10 vllm api calls within a asyncio.gather we made them share the same prompt until the end where the queries/instruction prompts differ. These call

arXiv:2609.37725v1 Announce Type: new Abstract: We introduce Context Language Models (CLMs), language models that natively manage their own context. We implement this by treating the context as a file

arXiv:2609.36116v1 Announce Type: new Abstract: We study how to build more capable general-purpose agents by extending large language models (LLMs) with native typed decision-making. We introduce Dyad

arXiv:2609.36927v1 Announce Type: new Abstract: Many computer tasks recur: the same workflow runs many times, with new inputs and from different starting states. Current computer-use agents re-plan ev

arXiv:2609.37970v1 Announce Type: cross Abstract: World-action models (WAMs) jointly predict how a scene will evolve and how an agent should act, however joint generation alone does not necessarily im

arXiv:2609.36201v1 Announce Type: cross Abstract: Computer-use agents (CUAs), while capable of completing computer tasks in everyday and professional workflows, can cause unintended harm even under be

Small teams are taking on more with AI—from finding customers to building products and managing finances. Our new report explores how small businesses are putting AI agents to work. And through a new

arXiv:2609.36852v1 Announce Type: new Abstract: Trajectory prediction is a key component for understanding human behavior patterns in dynamic scenes. Researchers have devoted substantial efforts to mo