Search: “agents”

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arXiv:2607.02911v1 Announce Type: cross Abstract: LLM-based coding agents solve software-engineering tasks through iterative interactions with development environments, where returned observations acc

arXiv:2607.05297v1 Announce Type: new Abstract: Recent LLM agents tackle increasingly long-horizon, open-ended tasks, and external skills, reusable procedural knowledge supplied to the agent, further

arXiv:2505.20203v4 Announce Type: replace Abstract: Many fear that future artificial agents will resist shutdown. I present an idea - the POST-Agents Proposal - for ensuring that doesn't happen. I pro

arXiv:2507.15903v2 Announce Type: replace-cross Abstract: Empowered by large language models (LLMs), intelligent agents have become a popular paradigm for interacting with open environments to facilit

arXiv:2606.22678v2 Announce Type: replace-cross Abstract: Agentic coding harnesses - such as Agent-Skills, Superpowers, and Agent-Rigor - are increasingly deployed to augment underlying LLMs for real-

arXiv:2507.05257v4 Announce Type: replace-cross Abstract: Recent benchmarks for Large Language Model (LLM) agents primarily focus on evaluating reasoning, planning, and execution capabilities, while a

arXiv:2606.29030v1 Announce Type: new Abstract: AI agents extend conventional large language model (LLM) applications by integrating language understanding with task execution, external tool use, and

Agentic security company Straiker Inc. today revealed that it has raised 64 million in new funding to expand a platform built that secures the artificial intelligence agents now spreading across enter

arXiv:2606.24437v1 Announce Type: new Abstract: Mixture-of-Agents (MoA) architectures improve inference-time scaling by organizing multiple LLM agents into layered reasoning pipelines. However, existi

arXiv:2606.11217v1 Announce Type: cross Abstract: The proliferation of large language models (LLMs) and autonomous AI agents has given rise to a rapidly growing methodological paradigm: 'in silico' be

arXiv:2606.11522v1 Announce Type: new Abstract: Autoresearch agents now propose, evaluate, and select scientific candidates against a metric, and that metric is usually an aggregate reduced over a het

arXiv:2606.10402v1 Announce Type: cross Abstract: Scientific discovery is often a collective process: researchers share partial results, inspect failed attempts, and build on each other's ideas over l

arXiv:2606.10209v1 Announce Type: new Abstract: Large language models deployed as autonomous agents for enterprise workflows face a key challenge: verbose tool responses from enterprise systems can ca

arXiv:2606.10749v1 Announce Type: cross Abstract: Large language model (LLM) agents are rapidly moving from conversational interfaces to software components that plan, invoke tools, maintain memory, a

arXiv:2404.02039v5 Announce Type: replace Abstract: Game environments provide rich, controllable settings that stimulate many aspects of real-world complexity. As such, game agents offer a valuable te

arXiv:2606.09316v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) enables agents to access external knowledge at inference time, but it primarily retrieves fragmented declarative ev

arXiv:2606.09826v1 Announce Type: cross Abstract: Vision-language model (VLM) agents are increasingly deployed in interactive game environments. Yet game benchmarks for VLM agents typically report a s

arXiv:2601.09923v3 Announce Type: replace Abstract: AI agents are vulnerable to prompt injection attacks, where malicious content hijacks agent behavior. Among proposed defenses, architectural isolati

arXiv:2606.02536v1 Announce Type: new Abstract: Text files such as skill files, memory files, and behavioral configuration files play a central role in defining how modern agents act. Through edits by

arXiv:2605.28617v1 Announce Type: new Abstract: LLM agents increasingly act by writing code, yet a split persists between the runtime that drives the agent and the code the model writes. The runtime o

arXiv:2506.08311v2 Announce Type: replace-cross Abstract: Automated Program Repair (APR) agents leverage Large Language Models (LLMs) to autonomously diagnose and fix software bugs through reasoning,

arXiv:2605.26195v1 Announce Type: cross Abstract: LLM-based agents are increasingly used for cybersecurity tasks, but most existing systems rely on fixed, human-designed scaffolds that struggle to ada

A full tour through RAG, document context, and AI agents - from 2023 to 2026 🌎🤖 @hexapode gave a comprehensive 90-min workshop at @aiDotEngineer Singapore last week that comprehensively traces through

arXiv:2512.18552v2 Announce Type: replace-cross Abstract: While current software agents powered by large language models (LLMs) and agentic reinforcement learning (RL) can boost programmer productivit

arXiv:2605.16303v1 Announce Type: cross Abstract: Large language models (LLM) agents may offer tools to predict human responses to surveys. A common technique for defining these agents uses only demog

arXiv:2605.16565v1 Announce Type: new Abstract: Skim is a speculative execution framework for web agents that exploits the predictable structure of purpose-built websites. Today's web-agent expense is

Recently @pinecone introduced Nexus – a new knowledge-engine layer for AI agents that reduces token use by up to 90%. It’s built on top of a vector database, but shifts reasoning earlier in the pipeli

LangSmith Engine feels like the missing piece for reliable agents. Clustering failures and suggesting targeted fixes turns raw traces into actionable improvements. This is how we scale agent developme

arXiv:2605.09721v1 Announce Type: cross Abstract: Tool-enabled AI agents are increasingly deployed in cloud-hosted environments and offered as services, where they perform side-effecting operations th

arXiv:2605.10913v1 Announce Type: new Abstract: We introduce Shepherd, a functional programming model that formalizes meta-agent operations on target agents as functions, with core operations mechaniz

arXiv:2509.03736v2 Announce Type: replace Abstract: The impressive capabilities of Large Language Models (LLMs) raise the possibility that synthetic agents can serve as substitutes for real participan

arXiv:2508.10880v3 Announce Type: replace-cross Abstract: The widespread deployment of LLM-based agents is likely to introduce a critical privacy threat: malicious agents that proactively engage other

arXiv:2605.05558v2 Announce Type: replace Abstract: A natural intuition about the economics of AI agents is that, because agents can be replicated at very low marginal cost, agent labor may be supplie

It’s 2:17 a.m., and your application monitor flags elevated database latency. Before your on-call engineer finishes reading the alert, three agents have already responded. The performance agent double

deep agents need the web, and it’s super exciting to team up with @LangChain to make that happen! Build agents with LangChain + @browserbase. Give your Deep Agents search, fetch, and browser subagents

This is the year of browser use agents!!! I'm so excited Build agents with LangChain + @browserbase. Give your Deep Agents search, fetch, and browser subagents to access the full web. All with full ob

Deep Agents is a framework or library developed by LangChain that enables the creation of sophisticated AI agents with enhanced reasoning capabilities. The project likely provides tools and abstractio

arXiv:2604.23392v1 Announce Type: new Abstract: Refereeing is vital in sports, where fair, accurate, and explainable decisions are fundamental. While intelligent assistant technologies are being widel

arXiv:2603.04855v3 Announce Type: replace Abstract: Student Personas (SPs) are emerging as infrastructure for educational LLMs, yet prior work often relies on ad-hoc prompting or hand-crafted profiles

A perfect example of how we use agents for internal tooling at LangChain: 𝚍𝚎𝚎𝚙𝚊𝚐𝚎𝚗𝚝𝚜 lets us keep our docs code fresh against a moving substrate great blog by @naomi_pen on how we're using deepagents

In this post, we show how connecting the Visier Workforce AI platform with Amazon Quick through Model Context Protocol (MCP) gives every knowledge worker a unified agentic workspace to ask questions i

Yutori Inc., a startup that develops autonomous artificial intelligence agents for everyday knowledge-work tasks on the web, today announced the launch of Delegate, which allows users to offload and “

As open-source platforms scramble to close the infrastructure gap, enterprises are discovering that autonomous operations expose a deeper problem than performance: control. The conversation around ent

arXiv:2602.01566v2 Announce Type: replace Abstract: Deep research is emerging as a representative long-horizon task for large language model (LLM) agents. However, long trajectories in deep research o

arXiv:2604.15713v1 Announce Type: cross Abstract: Type annotations are essential when printing terms in a way that preserves their meaning under reparsing and type inference. We study the problem of c