Search: “agents”

AIPC: Agent-Based Automation for AI Model Deployment with Qualcomm AI Runtime

arXiv:2604.14661v1 Announce Type: cross Abstract: Edge AI model deployment is a multi-stage engineering process involving model conversion, operator compatibility handling, quantization calibration, r

local-aiarxiv-cs-lg

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Formal Architecture Descriptors as Navigation Primitives for AI Coding Agents

DGX agent

arXiv:2604.13108v1 Announce Type: cross Abstract: AI coding agents spend a substantial fraction of their tool calls on undirected codebase exploration. We investigate whether providing agents with for

model-releasesarxiv-cs-ai

17 Apr 2026

Research

From Reactive to Proactive: Assessing the Proactivity of Voice Agents via ProVoice-Bench

arXiv:2604.15037v1 Announce Type: cross Abstract: Recent advancements in LLM agents are gradually shifting from reactive, text-based paradigms toward proactive, multimodal interaction. However, existi

researcharxiv-cs-cl

IE as Cache: Information Extraction Enhanced Agentic Reasoning

arXiv:2604.14930v1 Announce Type: new Abstract: Information Extraction aims to distill structured, decision-relevant information from unstructured text, serving as a foundation for downstream understa

agentsarxiv-cs-cl

MARS^2: Scaling Multi-Agent Tree Search via Reinforcement Learning for Code Generation

arXiv:2604.14564v1 Announce Type: cross Abstract: Reinforcement learning (RL) paradigms have demonstrated strong performance on reasoning-intensive tasks such as code generation. However, limited traj

Neuro-Oracle: A Trajectory-Aware Agentic RAG Framework for Interpretable Epilepsy Surgical Prognosis

model-releasesarxiv-cs-cl

arXiv:2604.14216v1 Announce Type: cross Abstract: Predicting post-surgical seizure outcomes in pharmacoresistant epilepsy is a clinical challenge. Conventional deep-learning approaches operate on stat

OpenMobile: Building Open Mobile Agents with Task and Trajectory Synthesis

model-releasesarxiv-cs-cl

arXiv:2604.15093v1 Announce Type: cross Abstract: Mobile agents powered by vision-language models have demonstrated impressive capabilities in automating mobile tasks, with recent leading models achie

Debate to Align: Reliable Entity Alignment through Two-Stage Multi-Agent Debate

arXiv:2604.13551v1 Announce Type: new Abstract: Entity alignment (EA) aims to identify entities referring to the same real-world object across different knowledge graphs (KGs). Recent approaches based

16 Apr 2026

Agentic Control in Variational Language Models

arXiv:2604.12513v1 Announce Type: new Abstract: We study whether a variational language model can support a minimal and measurable form of agentic control grounded in its own internal evidence. Our mo

local-aiarxiv-cs-lg

Cycle-Consistent Search: Question Reconstructability as a Proxy Reward for Search Agent Training

arXiv:2604.12967v1 Announce Type: new Abstract: Reinforcement Learning (RL) has shown strong potential for optimizing search agents in complex information retrieval tasks. However, existing approaches

SEW: Self-Evolving Agentic Workflows for Automated Code Generation

arXiv:2505.18646v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated effectiveness in code generation tasks. To enable LLMs to address more complex coding challenge

The A-R Behavioral Space: Execution-Level Profiling of Tool-Using Language Model Agents in Organizational Deployment

arXiv:2604.12116v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as tool-augmented agents capable of executing system-level operations. While existing benchmarks

Toward Autonomous Long-Horizon Engineering for ML Research

arXiv:2604.13018v1 Announce Type: new Abstract: Autonomous AI research has advanced rapidly, but long-horizon ML research engineering remains difficult: agents must sustain coherent progress across ta

agentsarxiv-cs-cl

MSA: Memory Sparse Attention for Efficient End-to-End Memory Model Scaling to 100M Tokens

arXiv:2603.23516v2 Announce Type: replace-cross Abstract: Long-term memory is a cornerstone of human intelligence. Enabling AI to process lifetime-scale information remains a long-standing pursuit in

Normative Common Ground Replication (NormCoRe): Replication-by-Translation for Studying Norms in Multi-Agent AI

arXiv:2603.11974v2 Announce Type: replace Abstract: In the late 2010s, the fashion trend NormCore framed sameness as a signal of belonging, illustrating how norms emerge through collective coordinatio

PICon: A Multi-Turn Interrogation Framework for Evaluating Persona Agent Consistency

arXiv:2603.25620v2 Announce Type: replace Abstract: Large language model (LLM)-based persona agents are rapidly being adopted as scalable proxies for human participants across diverse domains. Yet the

Plug-and-Play Dramaturge: A Divide-and-Conquer Approach for Iterative Narrative Script Refinement via Collaborative LLM Agents

arXiv:2510.05188v2 Announce Type: replace Abstract: Although LLMs have been widely adopted for creative content generation, a single-pass process often struggles to produce high-quality long narrative

local-aiarxiv-cs-ai

SEARL: Joint Optimization of Policy and Tool Graph Memory for Self-Evolving Agents

arXiv:2604.07791v2 Announce Type: replace Abstract: Recent advances in Reinforcement Learning with Verifiable Rewards (RLVR) have demonstrated significant potential in single-turn reasoning tasks. Wit

SecureVibeBench: Evaluating Secure Coding Capabilities of Code Agents with Realistic Vulnerability Scenarios

arXiv:2509.22097v3 Announce Type: replace-cross Abstract: Large language model-powered code agents are rapidly transforming software engineering, yet the security risks of their generated code have be

SkVM: Revisiting Language VM for Skills across Heterogenous LLMs and Harnesses

arXiv:2604.03088v3 Announce Type: replace-cross Abstract: LLM agents increasingly adopt skills as a reusable unit of composition. While skills are shared across diverse agent platforms, current system

agentsarxiv-cs-lg

TrajOnco: a multi-agent framework for temporal reasoning over longitudinal EHR for multi-cancer early detection

arXiv:2604.10386v1 Announce Type: new Abstract: Accurate estimation of cancer risk from longitudinal electronic health records (EHRs) could support earlier detection and improved care, but modeling su

WisPaper: Your AI Scholar Search Engine

arXiv:2512.06879v3 Announce Type: replace-cross Abstract: We present extsc{WisPaper}, an end-to-end agent system that transforms how researchers discover, organize, and track academic literature. The

Creator Incentives in Recommender Systems: A Cooperative Game-Theoretic Approach for Stable and Fair Collaboration in Multi-Agent Bandits

arXiv:2604.08643v1 Announce Type: new Abstract: User interactions in online recommendation platforms create interdependencies among content creators: feedback on one creator's content influences the s

safetyarxiv-cs-lg

13 Apr 2026

Exploring Teachers' Perspectives on Using Conversational AI Agents for Group Collaboration

arXiv:2602.07142v2 Announce Type: replace-cross Abstract: Collaboration is a cornerstone of 21st-century learning, yet teachers continue to face challenges in supporting productive peer interaction. E

13 Apr 2026

OpenKedge: Governing Agentic Mutation with Execution-Bound Safety and Evidence Chains

arXiv:2604.08601v1 Announce Type: new Abstract: The rise of autonomous AI agents exposes a fundamental flaw in API-centric architectures: probabilistic systems directly execute state mutations without

13 Apr 2026

AnomalyAgent: Agentic Industrial Anomaly Synthesis via Tool-Augmented Reinforcement Learning

arXiv:2604.07900v1 Announce Type: new Abstract: Industrial anomaly generation is a crucial method for alleviating the data scarcity problem in anomaly detection tasks. Most existing anomaly synthesis

agentsarxiv-cs-cv

AV-SQL: Decomposing Complex Text-to-SQL Queries with Agentic Views

arXiv:2604.07041v1 Announce Type: cross Abstract: Text-to-SQL is the task of translating natural language queries into executable SQL for a given database, enabling non-expert users to access structur

DosimeTron: Automating Personalized Monte Carlo Radiation Dosimetry in PET/CT with Agentic AI

arXiv:2604.06280v1 Announce Type: cross Abstract: Purpose: To develop and evaluate DosimeTron, an agentic AI system for automated patient-specific MC internal radiation dosimetry in PET/CT examination

EmoMAS: Emotion-Aware Multi-Agent System for High-Stakes Edge-Deployable Negotiation with Bayesian Orchestration

arXiv:2604.07003v1 Announce Type: new Abstract: Large language models (LLMs) has been widely used for automated negotiation, but their high computational cost and privacy risks limit deployment in pri

local-aiarxiv-cs-ai

Energy Saving for Cell-Free Massive MIMO Networks: A Multi-Agent Deep Reinforcement Learning Approach

arXiv:2604.07133v1 Announce Type: cross Abstract: This paper focuses on energy savings in downlink operation of cell-free massive MIMO (CF mMIMO) networks under dynamic traffic conditions. We propose

HY-Embodied-0.5: Embodied Foundation Models for Real-World Agents

model-releasesarxiv-cs-cv

arXiv:2604.07430v1 Announce Type: new Abstract: We introduce HY-Embodied-0.5, a family of foundation models specifically designed for real-world embodied agents. To bridge the gap between general Visi

LangDriveCTRL: Natural Language Controllable Driving Scene Editing with Multi-modal Agents

arXiv:2512.17445v2 Announce Type: replace Abstract: LangDriveCTRL is a natural-language-controllable framework for editing real-world driving videos to synthesize diverse traffic scenarios. It represe

safetyarxiv-cs-cv

ParseBench: A Document Parsing Benchmark for AI Agents

model-releasesarxiv-cs-cv

arXiv:2604.08538v1 Announce Type: new Abstract: AI agents are changing the requirements for document parsing. What matters is semantic correctness: parsed output must preserve the structure and

Visually-grounded Humanoid Agents

model-releasesarxiv-cs-cv

arXiv:2604.08509v1 Announce Type: new Abstract: Digital human generation has been studied for decades and supports a wide range of real-world applications. However, most existing systems are passively

BrowseSafe: Understanding and Preventing Prompt Injection Within AI Browser Agents

arXiv:2511.20597v2 Announce Type: replace-cross Abstract: The integration of artificial intelligence (AI) agents into web browsers introduces security challenges that go beyond traditional web applica

Dynamic Governance of Multi-LLM Agent Systems for Collaborative Conversational Outcomes

arXiv:2608.11207v1 Announce Type: new Abstract: When two LLM agents with structurally opposed objectives interact across multiple turns, the absence of a shared goal function produces not competition

Learning from Online User Feedback for Shopping Agents

arXiv:2608.11604v1 Announce Type: new Abstract: Large language model-based shopping agents are increasingly deployed in real-world e-commerce platforms, generating massive amounts of user interaction

Multi-Agent Embodied Autonomous Driving: From V2X Information Exchange to Shared World Models

arXiv:2606.13840v2 Announce Type: replace-cross Abstract: Autonomous driving is shifting from isolated vehicle intelligence toward multi-agent embodied systems that share perception, infer intent, and

safetyarxiv-cs-cv

ToolHazard: Scaling Adversarial Environments for Security Evaluation and Alignment of LLM-based Agents

arXiv:2608.11878v1 Announce Type: cross Abstract: Large language model (LLM) agents integrated with external tools are vulnerable to indirect prompt injections embedded in environmental states. Howeve

Towards a Formal Definition of Agent Memory: Basis, Span, Optimality, and the Sequential Memory Problem

arXiv:2608.11654v1 Announce Type: new Abstract: Despite the wide deployment of memory in large-model agents, there is no unified formal account of what a memory is or when it is optimal. This paper ta

safetyarxiv-cs-lg

GeoForge: Non-Parametric Self-Evolving Agents for Earth-Observation Reasoning

arXiv:2608.10494v1 Announce Type: new Abstract: Earth observation (EO) agents construct scientifically valid tool workflows and ground their conclusions in current geospatial evidence. This is challen

InSight-doc: Agentic Visual Perception for Long-Document Understanding

model-releasesarxiv-cs-cl

arXiv:2608.10628v1 Announce Type: cross Abstract: Long-document understanding often requires reasoning over many visually rich pages, making inference costly and prone to context rot. In this work, we

Research

Self-Correcting Long-Horizon Search Agents via Tree-Structured Memory

arXiv:2608.10676v1 Announce Type: new Abstract: Large language model (LLM)-based search agents answer questions through multi-step interactions with external environments. However, providing complete

researcharxiv-cs-ai

Research

SkillZip: Evaluation-Free Skill Compression for Self-Evolving Agents by Discovering Reusable Structure

arXiv:2608.11079v1 Announce Type: new Abstract: Self-evolving agents accumulate reusable skills by appending successful procedures and failure fixes. Over time, the same requirement is often restated

researcharxiv-cs-ai

Toward the Cognitive--Physical Limits of Embodied Intelligence through a World-Model-Centric Autonomous Racing Agent

arXiv:2608.10618v1 Announce Type: new Abstract: Embodied artificial intelligence aims to develop agents that perceive, reason, and act through continuous interaction with the physical world. However,

local-aiarxiv-cs-ro

ActBench: Self-Evolving Benchmark of Behavioral Safety in Cowork Agents

arXiv:2608.09476v1 Announce Type: cross Abstract: Cowork agents may complete benign tasks while disclosing protected data, manipulating unauthorized state, invocate unauthorized API. We define behavio

11 Aug 2026

Agentic AI-driven Immersive Simulation: A Knowledge-Aware Virtual Training Platform forHigh Dose Rate (HDR) Brachytherapy

arXiv:2608.08163v1 Announce Type: new Abstract: The convergence of the Metaverse and Large Language Model (LLM)-based AI agent is catalyzing a shift toward autonomous, immersive, and personalized peda

local-aiarxiv-cs-ai

11 Aug 2026

AIVV: Neuro-Symbolic LLM Agent-Integrated Verification and Validation for Trustworthy Autonomous Systems

arXiv:2604.02478v2 Announce Type: replace Abstract: Deep learning models excel at detecting anomaly patterns in normal data. However, they do not provide a direct solution for anomaly classification a