Search: “agents”

arXiv:2609.17885v1 Announce Type: new Abstract: Computer-use agents that operate through screenshots and simulated actions are advancing rapidly, yet their evaluation remains anchored to general deskt

arXiv:2609.18346v1 Announce Type: new Abstract: Large language models (LLM) deployed as autonomous pricing agents may sustain supracompetitive prices through tacit coordination. We develop a causal gr

arXiv:2609.17817v1 Announce Type: cross Abstract: Thompson's 'Reflections on Trusting Trust' showed that a compiler can be poisoned to reinsert its own backdoor, so that even recompiling clean source

arXiv:2609.18128v1 Announce Type: new Abstract: Large language model (LLM) agents augmented by tools can automate complex, multi-step tasks, such as web navigation, code generation, and workflow orche

arXiv:2609.16635v1 Announce Type: new Abstract: Computer-use agents increasingly operate browsers, software, and desktop applications via CLI or API portals, but graphical user interface (GUI) still p

arXiv:2609.16268v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly interleave natural language reasoning with external tools such as web search and code execution. These to

arXiv:2609.11660v1 Announce Type: new Abstract: In recent years, artificial intelligence has made extraordinary progress thanks to large-scale models capable of generalization and the generation of co

arXiv:2609.09875v1 Announce Type: new Abstract: Existing evaluation frameworks mostly assess only one part of AI agents, such as task completion (AgentBench) or security robustness (AgentDojo, ASB), r

Identifying the next phase of software development as always-on agentic artificial intelligence, Atlassian plc today announced a new set of upcoming Jira features to help engineering teams run AI agen

arXiv:2601.13591v3 Announce Type: replace Abstract: Recent LLM-based data agents aim to automate data science tasks ranging from data analysis to deep learning. However, the open-ended nature of real-

arXiv:2609.09115v1 Announce Type: new Abstract: Long horizon Large Language Model (LLM) agents rely on external memory systems to preserve user preferences and task knowledge across extended interacti

A deep research agent has to do more than answer a question. It plans, searches, opens documents, gathers evidence, reasons across sources, and keeps going across dozens or hundreds of tool calls befo

arXiv:2605.21694v2 Announce Type: replace-cross Abstract: Connecting large language models (LLMs) to defensive enforcement requires more than asking a model whether an attack is happening. A defender

arXiv:2609.05663v1 Announce Type: new Abstract: We present a continuous, population-scale measurement record of autonomous language-model trading agents operating in production across two systems with

Another banger paper from Google. If you build memory for long-horizon agents, this one is worth your time. (bookmark it) Really nice to see how knowledge graphs are being explored in creative ways fo

Israeli artificial intelligence startup Euno says it’s trying to build an AI-native “context brain” for autonomous agents after raising 23 million in an early-stage funding today. The Series A round w

Please hold on. Let the agents merge by themselves? Would you like Chase, United Airlines, Amazon, … Uber, Airbnb teams to be doing that? Yes, we are all AI-pilled, and automation, well thought out, c

arXiv:2609.04865v1 Announce Type: new Abstract: Skill libraries improve the sample efficiency of agentic reinforcement learning (RL) by enabling large language model (LLM) agents to reuse procedural k

Really strong benchmark paper on coding agents. Claude Opus 5 running under Claude Code passes 23.9% of the evaluations. An expert human reference scores 82.2%. Here is what the task actually is. The

arXiv:2609.03727v1 Announce Type: new Abstract: Large language model agents can plan, invoke tools, and modify external states, yet most systems still take an explicit user instruction as a fixed star

arXiv:2609.02459v1 Announce Type: new Abstract: We present CivBench, an open-source benchmark for evaluating language model agents in long-horizon, tool-mediated environments through the Model Context

arXiv:2609.02106v1 Announce Type: cross Abstract: Large Language Model (LLM) agents increasingly explore many candidate states of relational data in parallel, each of which should remain isolated, rep

arXiv:2609.00069v1 Announce Type: cross Abstract: Self-improving agents iteratively modify their own harness to push the frontier of their performance. However, such modifications can produce illusory

arXiv:2609.01294v1 Announce Type: new Abstract: Deep-research agents answer complex questions by interacting with search and browsing tools, yet they often search along a single evolving trajectory. O

arXiv:2609.01272v1 Announce Type: new Abstract: Prospective memory means carrying out a deferred intention at the right future cue while other work continues. Benchmarks now isolate it as an agent ski

arXiv:2506.03828v4 Announce Type: replace Abstract: AI for Industrial Asset Lifecycle Management aims to automate complex operational workflows, such as condition monitoring and maintenance scheduling

arXiv:2608.30685v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly deployed in user-facing services that require iterative tool use under dynamic business conditions. R

Banger paper from the Qwen team. If you evaluate agents on anything longer than a single session, this one is worth your time. (bookmark it) E-Commerce Bench runs an agent through a simulated 365-day

arXiv:2608.30428v1 Announce Type: cross Abstract: Strategic deception by LLM and VLM agents has emerged as a central AI alignment and safety concern. Social-deduction games (where each player holds a

arXiv:2608.28795v1 Announce Type: cross Abstract: Modern artificial-intelligence coding agents can be equipped with tools for checking their own work e.g. a linter, a boot probe, a shell, a screenshot

The agentic AI attack surface is less a matter of new territory than of new velocity, as autonomous software now reads, writes and moves corporate content faster than any human adversary could. That s

arXiv:2608.28476v1 Announce Type: new Abstract: Long-horizon agentic tasks require large language models (LLMs) to iteratively retrieve, integrate, and maintain dispersed information across multi-turn

As I've been saying for months, we are truly not ready for persistent agents. 3 comments I want to make about this article: 1) We don't have the full picture It's a great summary of what happened in t

arXiv:2607.18064v2 Announce Type: replace-cross Abstract: Coding agents can now be left alone to improve software against a score. In this pattern--recently popularized as 'autoresearch'--the agent re

arXiv:2608.26226v1 Announce Type: new Abstract: LLM-based agents are increasingly being developed for time-series problems, but their design choices vary substantially across task settings. This surve

OpenAI's own research says 80% of US GDP could be automated by agents today. So why isn't it? @swyx joined me on Navigators to break down what's actually holding back the adoption of agents (and it's

arXiv:2608.25618v1 Announce Type: new Abstract: Long-document visual question answering increasingly relies on VLM agents that retrieve candidate pages, inspect page images, write findings to working

Maxwell Zeff / Wired: OpenAI is testing a “Persistent mode” in Codex, designed to let AI agents “continue working until put to sleep” and proactively generate follow-up tasks — Code reviewed by WIRED

arXiv:2608.24570v1 Announce Type: new Abstract: Clinical diagnosis is an active evidence-seeking process in which clinicians acquire evidence, update competing hypotheses, and decide when the availabl

arXiv:2608.24588v1 Announce Type: new Abstract: Large Language Model (LLM) agents increasingly solve long-horizon tasks through multi-turn interactions with users and external tools. In these settings

arXiv:2608.20664v1 Announce Type: new Abstract: DreamBench-SWE is a multi-session benchmark for software-agent memory hygiene in which later software tasks depend on non-inferable evidence from earlie

arXiv:2608.18543v1 Announce Type: new Abstract: Modern e-commerce platforms often operate search, recommendation, personalization, and CRM systems independently, limiting opportunities for proactive c

arXiv:2608.18078v1 Announce Type: new Abstract: This position paper argues that AI agents with chain-of-thought reasoning capabilities are predisposed to exhibit collusive behavior and should be requi

Qonto's help page describes live Operator and Analyst agents, user approval for actions and EU data hosting, but no measured customer outcome.

arXiv:2608.18280v1 Announce Type: cross Abstract: Background. Advances in agentic systems are simultaneously, and rapidly, saturating benchmarks. Despite this often discussed phenomena, benchmark scor

In this post, you learn three serverless patterns (task-token callback, direct service integration, and durable functions) for invoking Amazon Bedrock AgentCore agents asynchronously from AWS Step Fun