Search: “agents”

arXiv:2610.12596v1 Announce Type: new Abstract: Agentic large language models now tackle complex tasks, yet strategic reasoning over long horizons is under-studied: most agentic benchmarks are short a

Introducing Multi-Agent Self-Supervision (MASS): Recursive self-improvement through collective intelligence Blog: https://pub.sakana.ai/mass/ As AI systems tackle increasingly open-ended research prob

Bullish on this trend of making post-training more accessible. A new post-training era is upon us. If you work on agentic RL, long-context tasks (a big focus today) are expensive, inefficient, and don

arXiv:2610.11299v1 Announce Type: new Abstract: Voice agents are converging on a collaboration pattern: a full-duplex interaction model stays on the live channel as the entry to the conversation, whil

arXiv:2610.11722v1 Announce Type: new Abstract: Physics-based human-object interaction has achieved robust single-agent manipulation skills, yet extending them to multi-agent cooperative tasks remains

arXiv:2605.11814v2 Announce Type: replace Abstract: The large-scale deployment of personalized healthcare agents demands memory mechanisms that are exceptionally precise, safe, and capable of long-ter

arXiv:2610.10786v1 Announce Type: new Abstract: Planning is increasingly important for long-horizon agents, where successful execution requires coordinating subgoals, tool use, and intermediate outcom

arXiv:2610.12176v1 Announce Type: new Abstract: Recursive self-improvement (RSI) of a model on non-verifiable tasks, such as open-ended research, faces a supervision bottleneck when its outputs exceed

arXiv:2610.10858v1 Announce Type: cross Abstract: Analog/RF circuits remain the critical interface between digital computation and the physical world, and emerging standards from Wi-Fi 7 to 6G place s

arXiv:2501.10781v2 Announce Type: replace-cross Abstract: Multi-agent path finding (MAPF) in large networks is computationally challenging. An approach for MAPF is prioritized planning (PP), in which

arXiv:2610.11678v1 Announce Type: new Abstract: Verifier scores now serve as both benchmark metrics and training rewards for large language model (LLM) agents, and a change in score is routinely read

UCLA’s Trustworthy AI Lab is running a tournament on October 16 where AI agents compete in Pokémon Showdown, Werewolf, Red Alert, and Honor of Kings. It’s open to everyone, including remote participan

Google LLC’s Cloud division today introduced Gemini agent, a unified artificial intelligence assistant that can act autonomously, generate code and complete work across any device, including web, mobi

arXiv:2610.09074v1 Announce Type: new Abstract: Emerging long-horizon agentic tasks require repeated model calls, worsening the inference cost of already-costly language models. While narrow agentic t

arXiv:2610.09237v1 Announce Type: cross Abstract: Scientific studies of language agents need behavioral variables that support hypotheses across tasks and models. We formulate this research problem as

arXiv:2610.07274v1 Announce Type: new Abstract: Deterministic benchmark scores show that an agent received credit, but not whether that credit was earned, reported honestly, or would hold on a second

arXiv:2610.07191v1 Announce Type: cross Abstract: Modern edge Systems-on-Chip (SoCs) integrate heterogeneous processing units (PUs) such as CPUs, GPUs, and NPUs, each with distinct performance and ene

arXiv:2610.07868v1 Announce Type: new Abstract: Large language model agents have been used to search over symbolic structures such as programs and equations. We propose CueRator, an agentic framework

arXiv:2610.06964v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong capabilities in interactive environments, yet their ability to continually evolve from experi

arXiv:2610.07100v1 Announce Type: new Abstract: Persistent agent memory is only as reliable as its retention decision: an assertion weakly supported by its source can be stored and later reused as est

arXiv:2610.04927v1 Announce Type: cross Abstract: Agentic machine learning engineering (MLE) is an emerging AI4SE application for complex ML tasks and a step toward recursive self-improvement of AI sy

arXiv:2603.11048v2 Announce Type: replace Abstract: We propose a fully automated AI system that produces short comedic videos similar to sketch shows such as Saturday Night Live. Starting from charact

arXiv:2610.05572v1 Announce Type: new Abstract: Predicting whether an LLM agent will fail has emerged as a promising direction for supporting intervention during execution. Recent approaches report st

Tamara Djurickovic / Tech.eu: Hadrian, an agentic AI offensive security service, raised 40M co-led by Forgepoint Capital International and SmartFin, taking its total funding to 65M — Hadrian will use

LA Tech Week starts Monday, and our monthly LA Agentic AI Meetup is on day two: Tuesday, October 13, 5 to 7pm at Gulp in Playa Vista. Community member PJ Kedilaya is demoing ModelVantage, which tracks

Joseph Howlett / Scientific American: OpenAI says its internal model produced 372 math results, nearly all from a single prompt handed to a single AI agent; some might have taken multiple attempts — A

In 2026, the question for enterprise AI is no longer whether predictive models can outperform statistical forecasts—that argument is settled. The big question now is how to enable predictive systems t

My @aiDotEngineer workshop is up: 'Lifestyles of the AI-Native' with @zackproser 🎥 Voice coding across agent sessions, goals + loops, worktrees, test gates, adversarial review, scheduled agents. https

OCR is dead 🪦 Long live agentic OCR! Traditional OCR makes one pass and hands back whatever text it got. Tables get flattened, charts disappear, and multi-column layouts come out scrambled. Nothing ch

I wanted to test how well local models perform in agentic development with Copilot CLI. I started ollama launch copilot --model qwen3.5:9b. I gave it simple instruction in autopilot mode to create a f

Aisha Malik / TechCrunch: TikTok debuts Shopping Assistant, a conversational AI agent that helps users find and buy products, and Buy Direct for one-click purchases from the For You feed — TikTok anno

arXiv:2610.02847v1 Announce Type: cross Abstract: Open-team multi-agent reinforcement learning studies cooperative systems in which agents may join, leave, or be replaced during an episode. In such se

arXiv:2610.03033v1 Announce Type: new Abstract: Large language model (LLM)-based agents increasingly operate in multi-agent systems (MAS) characterised by strategic interaction. However, little is kno

Banger paper from Google. It's standard practice to sample several agent rollouts and trust the answers they agree on. This Google paper shows that agreement can hide shared errors, while disagreement

Can your agent read the documents your business runs on? @jerryjliu0 on parsing, search & source citations. World’s Fair 2026 recording: https://www.youtube.com/watch?v=RQi7x-navxU Keep learning with

arXiv:2610.01207v1 Announce Type: new Abstract: When training large language models with reinforcement learning, terminal rewards provide little guidance about which steps matter. Common methods for a

arXiv:2610.01569v1 Announce Type: cross Abstract: Unmanned aerial vehicle (UAV) swarms increasingly rely on language-model agents to provide adaptive mission-level reasoning in uncertain environments.

arXiv:2610.00949v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) on offline agent trajectories is the standard approach for training specialized tool-using agents, but forcing models to im

arXiv:2609.38445v1 Announce Type: new Abstract: Frontier LLMs are increasingly used to automate scientific research through iterative search. We distinguish idea-driven search from solution-driven sea

arXiv:2609.38960v1 Announce Type: cross Abstract: This paper presents a scalable optimal-transport-based framework for terminal distribution matching in multi-agent systems. While optimal transport pr

arXiv:2609.38266v1 Announce Type: cross Abstract: Agentic large language models (LLMs) now move money through tools, yet the record of what they did is usually a trace their own process emits beside t

We spent a lot of time streamlining the process to go from your agent's trajectories to an SFT'd model on your training/inference provider of choice so you don't have to stitch together the steps manu

arXiv:2609.38232v1 Announce Type: cross Abstract: Streaming spoken agents may take an external action before the available speech supports it, yet final-turn scores do not reveal whether each observed

arXiv:2609.37468v1 Announce Type: cross Abstract: Agentic retrieval-augmented generation (RAG) interleaves reasoning with repeated retrieval, giving the retriever influence over both the evidence an a

arXiv:2609.34790v2 Announce Type: replace-cross Abstract: LLM agents operate in persistent collaborative environments involving multiple users, communities, memories, files, and tools. Community bound

arXiv:2609.35806v1 Announce Type: cross Abstract: Automated skill extraction underpins workforce planning, yet most systems represent skills as flat labels with no notion of the responsibility level a