Search: “agents”

arXiv:2604.03675v2 Announce Type: replace Abstract: Agentic search enables language models to solve knowledge-intensive tasks by adaptively acquiring external evidence over multiple steps. Reinforceme

Artificial intelligence customer service platform provider Quiq Inc. today launched a new voice product and refreshed its brand, betting that customer experience teams are ready to move beyond isolate

arXiv:2605.06230v2 Announce Type: replace Abstract: As large models evolve from conversational assistants into autonomous agents, challenges increasingly arise from long-horizon decision making, tool

This post describes a project where the developer created an autonomous AI agent capable of modifying and executing its own source code across a 7-day development period, integrating multiple language

arXiv:2605.03537v1 Announce Type: cross Abstract: This paper presents a modular AI agentic skill pipeline for automating subject indexing with Library of Congress Subject Headings (LCSH). Subject inde

arXiv:2502.10148v3 Announce Type: replace Abstract: Cooperative multi-agent reinforcement learning (MARL) struggles with sample efficiency, interpretability, and generalization. While Large Language M

arXiv:2605.03242v1 Announce Type: new Abstract: Tool-using agent systems powered by large language models (LLMs) are increasingly deployed across web, app, operating-system, and transactional environm

arXiv:2605.03383v1 Announce Type: new Abstract: Lithology classification aims to infer subsurface rock types from well-logging signals, supporting downstream applications like reservoir characterizati

arXiv:2605.03604v1 Announce Type: cross Abstract: This paper asks whether large language models (LLMs) can be used to study the strategic foundations of conflict and cooperation. I introduce LLMs as e

arXiv:2605.04019v1 Announce Type: new Abstract: AI systems are entering critical domains like healthcare, finance, and defense, yet remain vulnerable to adversarial attacks. While AI red teaming is a

arXiv:2605.03034v1 Announce Type: new Abstract: Agentic systems involved in high-stake decision-making under adversarial pressure need formal guarantees not offered by existing approaches. Motivated b

arXiv:2605.01740v1 Announce Type: cross Abstract: An agentic-AI runtime issues tool calls, sends messages, and actuates devices on behalf of an LLM. Catching the four ways an action can diverge from i

arXiv:2605.01394v1 Announce Type: cross Abstract: Formal specification is essential for rigorous program verification, yet writing correct specifications remains costly and difficult to automate. Alth

arXiv:2605.01507v1 Announce Type: new Abstract: Prior studies report that partial driving automation can increase the cognitive demands on human drivers. This effect largely arises from human drivers'

arXiv:2605.01471v1 Announce Type: cross Abstract: Maintaining reliable UI test suites in large-scale enterprise applications is a persistent and costly challenge. We present an industrial case study o

arXiv:2605.00914v1 Announce Type: cross Abstract: Multi-agent debate, where teams of LLMs iteratively exchange rationales and vote on answers, is widely deployed under the assumption that peer review

arXiv:2605.01970v2 Announce Type: cross Abstract: Memory systems enable otherwise-stateless LLM agents to persist user information across sessions, but also introduce a new attack surface. We characte

arXiv:2605.02463v1 Announce Type: cross Abstract: Multi-agent LLM systems are increasingly used to solve complex tasks through decomposition, debate, specialization, and ensemble reasoning. However, t

arXiv:2601.06034v1 Announce Type: cross Abstract: Software testing is critical in the software development lifecycle, yet translating requirements into executable test scripts remains manual and error

arXiv:2605.01675v1 Announce Type: cross Abstract: Constraint Programming (CP) is a powerful paradigm for solving combinatorial problems, yet translating natural language problem descriptions into exec

arXiv:2605.01299v1 Announce Type: new Abstract: Geometric Algebra (GA) presents challenges to learners due to its highly abstract mathematical structure and complex operational rules, as translating a

arXiv:2505.10887v3 Announce Type: replace Abstract: This paper introduces extsc{InfantAgent-Next}, a generalist agent capable of interacting with computers in a multimodal manner, encompassing text, i

arXiv:2508.12232v3 Announce Type: replace-cross Abstract: Issue-to-commit link recovery in software repositories is fundamental to software traceability and project management, yet it remains a challe

arXiv:2510.08804v3 Announce Type: replace Abstract: We present MOSAIC, a multi-agent Large Language Model (LLM) framework for solving challenging scientific coding tasks. Unlike general-purpose coding

arXiv:2605.02168v1 Announce Type: cross Abstract: Language model (LM)-based agents have demonstrated promising capabilities in automating complex tasks from natural language instructions, yet they con

arXiv:2605.01416v1 Announce Type: cross Abstract: The increasing scale and complexity of online platforms raises critical policy questions around harmful content, digital well-being, and user autonomy

The AI Engineer World's Fair is a conference event featuring talks on emerging AI research and engineering topics including autoresearch systems, advanced memory architectures, world models, tokenizat

arXiv:2604.27725v1 Announce Type: cross Abstract: A long-standing challenge in economics lies not in the lack of intuition, but in the difficulty of translating intuitive insights into verifiable rese

arXiv:2604.26962v1 Announce Type: cross Abstract: Education represents one of the most promising real-world applications for Large Language Models (LLMs). However, conventional tutoring systems rely o

arXiv:2604.27309v1 Announce Type: new Abstract: Clinical AI systems require not just point-in-time evaluation but continuous governance: the ongoing practice of monitoring, evaluating, iterating, and

arXiv:2604.27351v1 Announce Type: new Abstract: Agentic large language model systems have demonstrated strong capabilities. However, their reliance on language as the universal interface fundamentally

arXiv:2604.27150v1 Announce Type: new Abstract: Autonomous crypto trading systems often spend most of their design effort on finding entries, while exits are left to fixed rules that are rarely tested

arXiv:2602.07408v2 Announce Type: replace Abstract: Predicting gene regulation responses to biological perturbations requires reasoning about underlying biological causalities. While large language mo

arXiv:2604.28093v1 Announce Type: new Abstract: Terminal-agent benchmarks have become a primary signal for measuring the coding and system-administration capabilities of large language models. As the

In corporate parlance, any metric on a chart that shows rapid, significant growth over a short period of time is known as a “hockey stick.” On Wednesday, Stripe Inc. Chief Executive Patrick Collison s

arXiv:2604.25980v1 Announce Type: cross Abstract: In the context of quantum secure scenarios, existing research on mobile edge devices and intelligent computing and edge (ICE) systems based on the Non

Aviatrix Inc. today announced the launch of a new platform designed to contain artificial intelligence agents and enforce security controls and communications across AI workloads without changing AI a

arXiv:2604.24929v1 Announce Type: new Abstract: Agent benchmarks remain largely English-centric, while their multilingual versions are often built with machine translation (MT) and limited post-editin

arXiv:2603.04751v2 Announce Type: replace Abstract: Integrating web search tools has significantly extended the capability of LLMs to address open-world, real-time, and long-tail problems. However, ev

arXiv:2604.24549v1 Announce Type: cross Abstract: Coordinating large populations of grid-edge devices requires learning methods that remain fully decentralised in deployment while still respecting thr

arXiv:2508.19679v2 Announce Type: replace Abstract: Recent advances in Vision-Language Models (VLMs) have enabled mobile agents to perceive and interact with real-world mobile environments based on hu

arXiv:2506.20332v4 Announce Type: replace Abstract: Vision-language model-based mobile agents have gained the ability to understand complex instructions and mobile screenshots, benefiting from reinfor

arXiv:2512.15930v2 Announce Type: replace-cross Abstract: Intrinsically disordered proteins (IDPs) represent crucial therapeutic targets due to their significant role in disease -- approximately 80% o

arXiv:2509.13021v2 Announce Type: replace-cross Abstract: This work introduces xOffense, an AI-driven, multi-agent penetration testing framework that shifts the process from labor-intensive, expert-dr

arXiv:2604.22256v1 Announce Type: cross Abstract: Goal recognition aims to infer an agent's goal from observations of its behaviour. In realistic settings, recognition can benefit from exploiting hier

arXiv:2604.22191v1 Announce Type: cross Abstract: In agentic workflows, LLMs frequently process retrieved contexts that are legally protected from further training. However, auditors currently lack a