Search: “agents”

arXiv:2507.04227v2 Announce Type: replace-cross Abstract: Recent years have witnessed a rapid development of mobile GUI agents powered by large language models (LLMs), which can autonomously execute d

arXiv:2604.10842v1 Announce Type: cross Abstract: LLM-powered coding agents increasingly rely on tool-use protocols such as the Model Context Protocol~(MCP) to read and write files on a developer's wo

arXiv:2604.07789v1 Announce Type: cross Abstract: Recent advances in language model (LM) agents have significantly improved automated software engineering (SWE). Prior work has proposed various agenti

And that is what Thoth uses for its agents in the backend. Thanks for your contributions to oss @LangChain @hwchase17 https://github.com/siddsachar/Thoth AI that doesn't just work for you, it knows yo

Deep Agents or @LangChain? Just use the right tool for the right job great q! deepagents has more 'batteries included', which langchain v1 is a very minimalistic agent harness if you are doing more co

A Reddit discussion thread on r/MachineLearning in which practitioners explore how foundational concepts from Sutton and Barto's *Reinforcement Learning: An Introduction* — including MDPs, policy g...

deepagents now supports gemini 4 argon from @GoogleDeepMind! it supports 1M input tokens, long decode (up to 1M), and agentic video understanding! docs: https://docs.langchain.com/oss/python/integrati

arXiv:2606.12674v2 Announce Type: replace Abstract: Small language models (1.5B-4B parameters) offer low-cost, low-latency tool use but often produce plausible plans that fail during execution due to

arXiv:2610.22273v1 Announce Type: cross Abstract: Reasoning over long document contexts remains a challenge for large language models (LLMs). Standard retrieval methods are inherently reactive, bottle

arXiv:2610.21091v1 Announce Type: new Abstract: Agent memory enables large language model (LLM) agents to reuse past experiences without updating their parameters. However, semantic similarity alone d

arXiv:2610.21082v1 Announce Type: new Abstract: Large language model (LLM) agents can keep scientific experiments running for months with little human supervision, but reliable autonomous research als

arXiv:2610.16998v1 Announce Type: new Abstract: Deep search enables language agents to solve complex information-seeking tasks through iterative web exploration. However, developing robust open-source

arXiv:2610.18092v1 Announce Type: new Abstract: Deep research (DR) agents address open-ended information needs through multi-step reasoning, long-horizon web search, and evidence synthesis. However, e

arXiv:2610.14956v1 Announce Type: new Abstract: The Model Context Protocol provides a shared interaction substrate for the agentic web, allowing heterogeneous services to expose capabilities through a

I was curious about OpenResearch by alphaXiv. 'Turn your coding agents into research agents'? Sounds great! Just what I needed to save time on my experiments. So I copy pasted their repo into Claude a

Observability and information technology management software company SolarWinds Worldwide LLC today unveiled Avior, a standalone agentic artificial intelligence system built to take on first-line oper

Agentic artificial intelligence startup Uvi said today it has raised 7.5 million in seed funding to tackle an expensive problem around business context that’s draining millions of dollars annually fro

Katie Roof / Business Insider: Sources: Decagon, which offers AI customer service agents and was last valued at $4.5B, hired a bank and is in early talks with buyers, including ServiceNow — Buzzy AI a

arXiv:2610.12655v1 Announce Type: new Abstract: LLM agents can execute increasingly complex tasks, but effective assistance also requires aligning their actions with goals and constraints that users m

arXiv:2605.11928v2 Announce Type: replace Abstract: Tool-use language agents are evaluated on benchmarks that assume clean inputs, unambiguous tool registries, and reliable APIs. Real deployments viol

arXiv:2610.09240v1 Announce Type: cross Abstract: Modern web agents built on large vision-language models process webpages, select relevant UI elements, and translate model outputs into browser action

arXiv:2610.09858v1 Announce Type: new Abstract: Large language model agents tackle multi-step tasks by interleaving reasoning and tool calls with observations from the environment. Prior work has show

Atlassian Corp. today announced Agentic Multiplayer Protocol, a platform update designed to change how humans and artificial intelligence agents collaborate and get work done using shared context and

arXiv:2610.07459v1 Announce Type: new Abstract: Organizations make claims about their AI agents: a person approves every external email, every action is logged, an evaluation shows the agent is safe t

arXiv:2610.07557v1 Announce Type: cross Abstract: Static-analysis checker synthesis requires agents to interpret a defect specification, inspect a repository, implement analyzer-specific logic, and re

arXiv:2610.04494v1 Announce Type: cross Abstract: Testing deep reinforcement learning (DRL) agents in cyber-physical systems aims to uncover diverse failures before deployment, but each execution can

Dutch offensive security startup Hadrian Security B.V. today announced that it has raised 40 million in new funding to expand its business internationally. Hadrian’s software points artificial intelli

arXiv:2610.02425v1 Announce Type: new Abstract: Static evaluations credit a language model for naming the right move, but an agent must carry a plan through to a verified outcome while an opponent res

arXiv:2610.02627v1 Announce Type: new Abstract: An email assistant should not complete less work simply because a user phrases the same request differently. Yet most benchmarks test each task with onl

Banger paper from NVIDIA on long running agents. A model can accept 128K tokens of context and still make more mistakes the longer it works through a task. If your agent loses its place partway throug

arXiv:2610.00511v1 Announce Type: new Abstract: Before a difficult decision, people often act simply to understand the situation better. We turn an object to see another side, place alternatives next

arXiv:2610.01415v1 Announce Type: new Abstract: Large language model (LLM) agents can now undertake increasingly complex tasks, but the way they organize interaction history into memory does not ensur

arXiv:2610.00609v1 Announce Type: new Abstract: Legal research is a core and time-consuming legal workflow. Lawyers must identify controlling authority, verify that it remains valid, reconcile statute

arXiv:2610.00557v1 Announce Type: cross Abstract: Autonomous red team agents increasingly stress-test AI-enabled cyber defenses by planning strategy and executing multistage attacks. Reinforcement lea

arXiv:2609.40353v1 Announce Type: new Abstract: The task of 3D assembly requires translating an understanding of parts and their relationships into precise spatial arrangements. Can pretrained general

arXiv:2609.39101v1 Announce Type: new Abstract: Equipping VLM agents with world modeling capabilities has shown strong potential for complex reasoning and long-horizon planning, while reducing the dep

arXiv:2609.38812v1 Announce Type: new Abstract: Terminal agents rely on self-verification to assess and correct their solutions as they solve tasks through interaction with command-line environments.

arXiv:2609.33665v2 Announce Type: replace Abstract: Automatically generated environments provide a scalable source of interaction data for training general agents. However, existing approaches mainly

arXiv:2609.38334v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as agents for multi-step decision-making, yet transfer poorly to unseen environments. World-model

arXiv:2609.39982v1 Announce Type: cross Abstract: Terminal agents act through stochastic model generations, yet the ability to generate a useful action does not ensure its reliable execution. A poor c

arXiv:2609.37176v1 Announce Type: new Abstract: Computer-use agents have become increasingly capable of executing tasks on live desktops through natural-language instructions, based on trajectories of

arXiv:2609.36488v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong performance on complex web navigation tasks, yet they remain brittle in real-world settings w

How many people show up on a Tuesday night to talk about document processing for AI agents? 🤔 In New York, enough to fill the room and start a waitlist. In San Francisco, almost 600. We were in both c

arXiv:2609.37311v1 Announce Type: new Abstract: Recent Recommendation Agents (RecAgents) offer a promising alternative by shifting recommendation to an active, user-side paradigm, where generative age

arXiv:2609.35402v1 Announce Type: new Abstract: When pricing agents meet repeatedly on a platform, the platform decides who faces whom. We ask whether that choice moves the prices the agents learn, an

arXiv:2609.32918v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly being used in scientific workflows, but their ability as agents to directly control laboratory experime