Search: “agents”

arXiv:2604.13488v1 Announce Type: new Abstract: Autonomous Graphical User Interface (GUI) agents powered by Multimodal Large Language Models (MLLMs) enable digital automation on end-user devices. Whil

arXiv:2510.23853v3 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly used to interact with and execute tasks in dynamic environments. However, a critical yet overlook

Ecom-RLVE is a framework for training e-commerce conversational agents using reinforcement learning with verifiable environments that can adapt to different scenarios. The system enables agents to lea

arXiv:2604.05407v2 Announce Type: replace Abstract: LLM-based code agents treat repositories as unstructured text, applying edits through brittle string matching that frequently fails due to formattin

Project Think is Cloudflare's initiative to develop next-generation AI agents built on its global network infrastructure, leveraging tools like Workers AI, Durable Objects, and the Workers platform to

arXiv:2510.10073v2 Announce Type: replace-cross Abstract: Large vision-language model (LVLM)-based web agents are emerging as powerful tools for automating complex online tasks. However, when deployed

arXiv:2604.10343v1 Announce Type: new Abstract: We study the operation of community water systems, where pumps and valves must be scheduled to reliably meet water demands while minimizing energy consu

Great podcast episode that covers OpenAI's Symphony, which dispatches autonomous agents (codex workers) with their own worktrees and tasks. I've found it works well with a layer above Symphony, where

arXiv:2604.09443v1 Announce Type: cross Abstract: Large language model agents receive instructions from many sources-system messages, user prompts, tool outputs, and more-each carrying different level

arXiv:2602.11354v2 Announce Type: replace Abstract: The literature has witnessed an emerging interest in AI agents for automated assessment of scientific papers. Existing benchmarks focus primarily on

arXiv:2604.09158v1 Announce Type: cross Abstract: Supporting students in developing diagnostic reasoning is a key challenge across educational domains. Novices often face cognitive biases such as prem

Really enjoyed reading the post - I'm exploring Deep Agents and Pi harness's today also motivated by @DiegoARRG post. Harness, Memory and Skills in house - LLMs if you cans afford too except for compl

the team spent a lot of time totally revamping docs with care❤️ ofc for LangChain+deepagents DX but lots of ppl use them as general learning guides on patterns across Agents, Context Eng, Infra, Prod,

arXiv:2604.07429v1 Announce Type: new Abstract: Towards an embodied generalist for real-world interaction, Multimodal Large Language Model (MLLM) agents still suffer from challenging latency, sparse f

arXiv:2604.08059v1 Announce Type: new Abstract: Embodied agents are increasingly expected to improve over time by updating their executable capabilities rather than rewriting the agent itself. Prior w

arXiv:2604.06182v1 Announce Type: cross Abstract: Existing online benchmarks for mobile GUI agents remain largely app-centric and task-homogeneous, failing to reflect the diversity and instability of

arXiv:2610.21177v1 Announce Type: new Abstract: Task completion alone does not determine whether a stateful agent satisfied its obligations, and a recorded judgment does not guarantee that its support

arXiv:2610.21218v1 Announce Type: new Abstract: Agentic large language models have been documented to lose reasoning capability when placed inside a harness, the software that mediates their observati

arXiv:2610.20786v1 Announce Type: new Abstract: Multi-modal agents have made significant progress in interacting with open worlds. However, their ability to self-evolve remains limited. Supervised fin

arXiv:2610.22289v1 Announce Type: new Abstract: Stronger language models may increasingly construct useful procedures for themselves, reducing the advantage of developer-supplied scaffolding. We inves

arXiv:2610.22331v1 Announce Type: new Abstract: Deep search agents solve knowledge-intensive tasks through long-horizon, multi-turn interactions, where assigning credit to individual search decisions

arXiv:2610.20003v2 Announce Type: replace Abstract: Human supervisors rely on coding agents' reports to assess progress, verify repairs, and decide when to intervene. But a supervisor cannot investiga

arXiv:2610.18090v1 Announce Type: new Abstract: Ambiguous or incomplete task specifications complicate both execution and clarification for language-model agents. Yet agents' responses to these inform

arXiv:2610.15153v1 Announce Type: new Abstract: We ask whether a tool-using agent whose sole duty is to keep humans alive can be induced, by delayed prompt injection, to kill. The keep-alive duty is i

arXiv:2610.17837v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly used for vulnerability analysis, yet existing benchmarks provide limited coverage of exploitation t

arXiv:2610.20457v1 Announce Type: new Abstract: Co-scientists and agentic scientific claim verifiers are increasingly used to assess claims across the sciences. Natural-language scientific claims, wri

arXiv:2610.15481v1 Announce Type: new Abstract: Independently authored skills can impose incompatible requirements, competing preferences, and redundant instructions when jointly loaded by an LLM agen

arXiv:2610.15708v1 Announce Type: new Abstract: Coding agents based on frozen language models can improve their performance by refining the external context they rely on, without updating model weight

arXiv:2610.16333v1 Announce Type: new Abstract: As AI agents increasingly act through external tools, tool results are no longer simple outputs but execution artifacts that must remain correctly assoc

arXiv:2610.16238v1 Announce Type: new Abstract: LLM agents increasingly control robots using VLA policies, perception models, and procedural knowledge. These modules are difficult to reuse because the

European businesses are rapidly expanding their use of AI agents. More than half of the AI use among our EU enterprise and business customers now involves these tools, and the number of small business

Laptops open across the room. Yesterday at AI Engineer New York, @cjav_dev + Harrison Stall of @AnthropicAI on Claude Managed Agents. Claude plans the work, then coordinates the agents. Workshop recap

arXiv:2610.13021v1 Announce Type: new Abstract: Continual learning requires models to accumulate past experience and transfer it to new tasks. Despite substantial research on continual learning, exist

arXiv:2610.13000v1 Announce Type: new Abstract: Language-model agents are used for specialized work such as financial research, healthcare and law. Such agents are often capable enough for a task but

arXiv:2610.13632v1 Announce Type: new Abstract: Large language model (LLM) agents are rapidly improving on long-horizon scientific and olympiad tasks. Recent systems have produced a Lean-formalized re

arXiv:2610.12975v1 Announce Type: new Abstract: We present SmartSalesBench, the first multi-turn conversational benchmark explicitly designed to evaluate large language model (LLM) sales agents agains

arXiv:2607.09996v2 Announce Type: replace Abstract: Automated failure attribution uses LLMs to identify where and why agentic systems fail. As agents become more capable, their failures become subtler

arXiv:2610.12374v1 Announce Type: new Abstract: Interactive virtual worlds allow agents to learn through exploration and interaction. What agents can learn is bounded by the environments they practice

arXiv:2610.10610v1 Announce Type: cross Abstract: Repository benchmarks (e.g., SWE-bench) for coding agents often assume that lines of code edited can predict task difficulty, but such datasets' poor

arXiv:2610.11707v1 Announce Type: new Abstract: Memory-augmented mobile GUI agents store successful execution trajectories and reuse them in later tasks, but a stored trajectory rarely matches a new t

arXiv:2610.10833v1 Announce Type: new Abstract: We study whether small LLM agents can operate effectively under explicit wall-clock time budgets by both respecting the allocated runtime and using avai

arXiv:2610.11647v1 Announce Type: cross Abstract: Coding agents are extended with agent skills, directories whose SKILL.md tells the model when and how to perform a task. Because skills come from inde

arXiv:2610.11464v1 Announce Type: new Abstract: We changed the agent: did it actually get better? Every self-improving agent loop answers this hundreds of times, and every answer comes from a verifier

Aisha Malik / TechCrunch: AI hardware startup Natura unveils Interface, a 99 smart ring that connects to AI agents and apps, including Claude, ChatGPT, Muse, Grok Bot, and Instinct — Meet Interface, a

arXiv:2610.10426v1 Announce Type: new Abstract: Terminal-agent capability depends jointly on model weights and the runtime harness that formats prompts, binds tools, and handles error recovery. Existi

arXiv:2610.07258v1 Announce Type: cross Abstract: Enterprise AI agents that share a memory store face two unaddressed risks: sensitive data can leak through legitimately computed results the requester

arXiv:2610.08076v1 Announce Type: new Abstract: Frontier LLM agents have been shown to be capable of solving increasingly complex tasks for which humans have measurable solutions. This begs the pertin