Search: “agents”

arXiv:2605.25422v1 Announce Type: cross Abstract: The convergence of large language models (LLMs) with 6G networks is fostering a paradigm of autonomous multi-agent cooperation, which in turn is expec

In this post, we provide a solution to build highly scalable, serverless multi-agent generative AI systems on AWS using LangGraph Agents as orchestrators integrated with Amazon Bedrock AgentCore Memor

arXiv:2605.25338v1 Announce Type: cross Abstract: Large language model (LLM) agents frequently fail on multi-step tasks involving reasoning, tool use, and environment interaction. While such failures

arXiv:2605.25188v1 Announce Type: new Abstract: Multi-agent LLM systems improve reasoning by combining outputs from multiple agents, but interaction-heavy methods can introduce error propagation and h

arXiv:2605.25421v1 Announce Type: new Abstract: Communication protocol design is a central challenge in large language model-based multi-agent systems. Existing single-channel approaches face an inher

New agent skill to convert YouTube videos to slides and notes. Just built an insane new agent skill. It can perfectly extract slides from YT videos, then write notes, images, transcripts, and slides i

arXiv:2605.24775v1 Announce Type: new Abstract: Operating LLMs as coordinated multi-agent research systems over multi-hour runs surfaces failure modes that single-shot evaluation cannot: upstream prov

arXiv:2605.24756v1 Announce Type: new Abstract: Language-model agents increasingly emit uncertainty signals throughout a trajectory, but existing agentic UQ evaluations often conflate ranking usefulne

Amid rapidly growing adoption of enterprise-level AI agents, there’s a disconnect emerging between ambition and execution. Although 85% of organizations say they want to be agentic within the next thr

arXiv:2605.23562v1 Announce Type: cross Abstract: Sparse rewards are a major bottleneck in multi-agent reinforcement learning (MARL), where simultaneous learning induces non-stationarity and makes rew

arXiv:2605.23590v1 Announce Type: new Abstract: ReAct-style agents for search-intensive, multi-step reasoning tasks rely largely on their own internal judgment to decide what evidence to seek, which r

arXiv:2605.23382v1 Announce Type: new Abstract: Agentic reinforcement learning (Agentic RL) has achieved strong progress in tasks with clear success signals. However, many real-world agent application

/goal is really insane! It's how you can get the most out of coding agents today. For efficiency, I find it works best when you do planning before /goal. This ensures the agent has the right context a

This article defines and clarifies key terminology related to AI agents, including the concepts of 'harness' and 'scaffold,' which are important architectural and operational components in building an

arXiv:2601.14652v5 Announce Type: replace Abstract: While multi-agent systems (MAS) promise elevated intelligence through coordination of agents, current approaches to automatic MAS design under-deliv

arXiv:2605.23179v1 Announce Type: new Abstract: Agentic AI orchestrators reduce the interface and assembly costs of composing information systems capabilities across organizational boundaries, seeming

arXiv:2602.01665v2 Announce Type: replace-cross Abstract: The design of environments plays a critical role in shaping the development and evaluation of cooperative multi-agent reinforcement learning (

Agents shouldn’t have direct visibility into env vars or credentials that can expose sensitive systems and data. Keeping secrets outside the agent’s context helps secure the env while still allowing a

Agents are too good at sounding right. And terrible at proving what actually happened, especially on complex, long-running tasks. So I built a fully traceable and forkable research agent with @yoheina

arXiv:2605.22138v1 Announce Type: cross Abstract: How should an agent decide when and how to plan? A dominant approach builds agents as reactive policies with adaptive computation (e.g., chain-of-thou

arXiv:2605.20608v1 Announce Type: new Abstract: Realizing Level 4/5 Autonomous Networks (AN) demands a shift from static automation to agent-native intelligence. Current operations, reliant on rigid s

arXiv:2605.22104v1 Announce Type: new Abstract: Real-world image restoration is challenging due to complex and interacting mixed degradations. Recent agent-based approaches address this problem by com

We're hosting an agentic AI meetup in LA on May 28th — 5–7pm at Gulp in Playa Vista. Builders, founders, engineers. Drinks, no fluff. RAG systems, agentic workflows, or just starting out — all welcome

arXiv:2605.20616v1 Announce Type: new Abstract: Language agents increasingly operate over streams of related tasks, yet existing memory systems struggle to convert accumulated experience into reusable

Cursor's new Composer 2.5 takes third on the Artificial Analysis Coding Agent Index and is ~10-60x lower cost than the higher-effort Opus 4.7 and GPT-5.5 variants above it. This release puts Composer

Release: datasette-agent 0.1a3 'View SQL query' buttons for both visible tables and collapsed SQL result tool calls. Don't display empty reasoning chunks Improved handling of truncated responses - tab

🆕Daytona’s Agent-Native Compute: 60ms sandboxes, 50K startups in 75 sec, 850K daily runs, RL/evals, CLI > MCP, & the end of localhost https://latent.space/p/daytona @daytonaio CEO @ivanburazin explain

@Replit longer form video on Active Graph [7 min 22 sec] - flip the agent architecture - 1970s blackboard system - rollback, fork, diff agent runs - experience + behaviors + beliefs = you - behaviors

arXiv:2605.18770v1 Announce Type: cross Abstract: We present a collaborative agentic GraphRAG framework for expert analysis of commercial registry data. Public registries are often formally accessible

This post references a previous article discussing stateful agents broadly, which served as inspiration for Yohei Nakajima's project. The post likely documents how earlier discourse on agent architect

arXiv:2605.19418v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) have demonstrated strong reasoning and decision-making capabilities that consistently surpass those of single LLM ag

Juicebox App Inc. today introduced a suite of autonomous recruiting agents that help hiring teams proactively identify and engage candidates across multiple open roles simultaneously, recommending pro

I highly recommend this. The Agentic Review is a new podcast from @QodoAI hosted by Itamar Friedman and Nnenna Ndukwe, and it's a great AI coding show that's neither hype nor doom. It's honest convers

ICYMI: LangSmith Sandboxes are GA ✅ Agents get a real filesystem, shell, and package manager. Isolated from your infra. ✅ Works with Deep Agents, Open SWE, or your own code. ✅ Auth with the same API k

arXiv:2605.19351v1 Announce Type: cross Abstract: Generative agents based on large language models reproduce believable human behavior in cooperative settings, but how they should reason in situations

we've been building agents around the llm, starting with conversations, adding tools, giving rules, logging everything, and storing a form of it as retrievable state Active Graphs flips this. what if

arXiv:2605.16265v1 Announce Type: new Abstract: The safety of autonomous AI agents is increasingly recognized as a critical open problem. As agents transition from passive text generators to active ac

arXiv:2605.18048v1 Announce Type: new Abstract: While Graphical User Interface (GUI) agents have shown promising performance in automated device interaction, they primarily depend on static parametric

arXiv:2605.17361v1 Announce Type: cross Abstract: Multi-agent systems (MAS) powered by large language models (LLMs) have emerged as a powerful paradigm for complex problem solving, where performance c

arXiv:2605.17444v1 Announce Type: cross Abstract: Modern software ecosystems face a rapidly growing number of disclosed vulnerabilities, increasing the need for automated repair techniques that can op

arXiv:2605.17283v1 Announce Type: cross Abstract: Recent progress in formal theorem proving has benefited from large-scale proof generation and verifier-aware training, but agentic proving is rarely i

Read more on what we've learned while developing long-horizon agent evals: Curious finding while creating evals and benchmarks for long-horizon (100+ turn) agents While it’s generally thought that a d

arXiv:2605.18684v1 Announce Type: cross Abstract: Legacy systems concentrate business rules, architectural decisions, and operational exceptions that often remain implicit in code, data, configuration

arXiv:2605.18401v1 Announce Type: cross Abstract: Long-horizon LLM agents leave traces that could become reusable experience, but raw trajectories are noisy and hard to govern. We treat Agent Skills a

At Google I/O, two dominant branding phrases emerged: 'agent-first,' emphasizing AI agents as a primary computing paradigm, and 'at the speed of voice,' highlighting voice-based interaction speed and

arXiv:2605.16269v1 Announce Type: cross Abstract: Modern military operations expose soldiers to sustained psychological stress, leading to acute reactions, post-traumatic stress symptoms, and other me