Search: “agents”

The Emerging Paradigm of Geospatial Foundation Models: From Pre-Training to Agentic Reasoning

arXiv:2607.12177v1 Announce Type: new Abstract: The analysis of satellite and aerial imagery has entered a new era with the advent of foundation models. This paper describes the concept of Geospatial

15 Jul 2026

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Who Grades the Grader? Co-Evolving Evaluation Metrics and Skills for Self-Improving LLM Agents

DGX agent

arXiv:2607.12790v1 Announce Type: new Abstract: Self-evolving agent systems improve by creating, revising, and retiring their own skills, but every such loop rests on a hidden assumption: a reliable e

safetyarxiv-cs-ai

15 Jul 2026

Context Graphs for Proactive Enterprise Agents

arXiv:2607.07721v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) and agentic frameworks have advanced enterprise AI considerably, yet agents remain fundamentally reactive: they wai

DeepSWE: Measuring Frontier Coding Agents on Original, Long-Horizon Engineering Tasks

model-releasesarxiv-cs-lg

arXiv:2607.07946v1 Announce Type: cross Abstract: DeepSWE is a benchmark of 113 original, long-horizon software engineering tasks for evaluating coding agents. Most public agentic coding benchmarks fo

MASTE: A Multi-Agent Pipeline for Zero-Shot Aspect Sentiment Triplet Extraction

arXiv:2607.08080v1 Announce Type: new Abstract: Aspect Sentiment Triplet Extraction (ASTE) requires jointly identifying (aspect, opinion, sentiment) triples from a given review sentence. While large l

agentsarxiv-cs-cl

Open-ended Multi-agent Autocurricula via Visual Inspection of Policies with Multi-modal LLMs

arXiv:2607.08193v1 Announce Type: cross Abstract: Open-ended curricula in Reinforcement Learning (RL) aim to train generally-capable agents by identifying tasks that facilitate learning increasingly c

Token-Flow Firewall: Semantic Runtime Auditing for Persistent AI Agents

arXiv:2607.08395v1 Announce Type: cross Abstract: Persistent AI agents extend large language models (LLMs) beyond single-turn interaction into long-lived software systems. Unlike traditional chat assi

local-aiarxiv-cs-cl

Beyond Attack-Success Rate: Action-Graded Severity Scale for Tool-Using AI Agents

arXiv:2607.07474v1 Announce Type: cross Abstract: Agentic red-teaming benchmarks report whether an injected agent was compromised as a single bit: the attack succeeded, or it did not. We argue that th

Entropy Pacing Policy Optimization for Multi-Task Agentic Reinforcement Learning

arXiv:2607.07178v1 Announce Type: cross Abstract: Recent breakthroughs of Reinforcement Learning (RL) have highlighted its potential for complex agentic Large Language Model (LLM) tasks. However, exis

Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows in Production

arXiv:2607.07052v1 Announce Type: cross Abstract: AI agents deployed for IT operations are typically permanent cost centers because every execution requires full LLM inference, even for previously sol

Security and Privacy in Agentic AI: Grand Challenges and Future Directions

arXiv:2607.06608v1 Announce Type: cross Abstract: We present key challenges and future research directions in the security and privacy of agentic AI, based on a horizon-scanning exercise that brought

SpaCellAgent: A Self-Evolving LLM-Based Multi-Agent Framework for Trajectory Analysis

arXiv:2607.07467v1 Announce Type: new Abstract: Spatial and Single-cell transcriptomics are transformative in deciphering cellular dynamics. As the fundamental paradigm for reconstructing cell develop

aiAuthZ: Off-Host, Identity-Bound Authorization for AI Agents

arXiv:2607.05518v1 Announce Type: cross Abstract: AI agents issue tool calls on the basis of text they cannot verify, so any party who controls part of the context can forge the appearance of authorit

Information Gain-based Rollout Policy Optimization: An Adaptive Tree-Structured Rollout Approach for Multi-Turn LLM Agents

arXiv:2607.06223v1 Announce Type: new Abstract: Reinforcement learning has become a promising paradigm for improving large language model (LLM) agents on long-horizon search tasks, where the agent mus

MASCA: LLM based-Multi Agents System for Credit Assessment

arXiv:2507.22758v2 Announce Type: replace Abstract: Recent advancements in financial problem-solving have leveraged LLMs and agent-based systems, with a primary focus on trading and financial modeling

safetyarxiv-cs-cl

MCP-Enabled Agentic AI for Autonomous IPoDWDM Network Lifecycle Automation

arXiv:2607.05975v1 Announce Type: cross Abstract: This demo presents an MCP-enabled agentic AI architecture for autonomous control of vendor-agnostic IPoDWDM networks. We demonstrate live end-to-end l

Reward as An Agent for Embodied World Models

arXiv:2606.19990v2 Announce Type: replace Abstract: While RL has become a promising tool for refining world models, existing methods largely rely on conservative rollouts near the training distributio

Task Decomposition-Guided Reranking for Adaptive Agent Skill Retrieval

arXiv:2607.06283v1 Announce Type: new Abstract: Skill usage can significantly enhance the ability of modern agent systems to complete complex tasks. However, the growing scale of skill libraries makes

The Balkanization of Execution-Security Research for AI Coding Agents: Isolation, Access Control, and Time-of-Check-to-Time-of-Use Vulnerabilities

arXiv:2607.05743v1 Announce Type: cross Abstract: AI coding agents now read repositories, call tools, and execute shell commands with limited human oversight, and a fast-growing body of work studies w

When Lower Privileges Suffice: Investigating Over-Privileged Tool Selection in LLM Agents

arXiv:2606.20023v2 Announce Type: replace-cross Abstract: As LLM agents increasingly select tools autonomously, their choices among tools with different privileges become safety-relevant. However, pri

Agentic and Generative AI for Open-Source Intelligence and Cyber Investigations: Taxonomy, Evaluation, Challenges, and Future Directions

arXiv:2607.03233v1 Announce Type: cross Abstract: The rapid growth of publicly available digital information has rendered manual open-source intelligence (OSINT) analysis insufficient for modern intel

EvoAgentBench: Benchmarking Agent Self-Evolution via Ability Transfer

arXiv:2607.05202v1 Announce Type: new Abstract: Agent self-evolution in long-horizon LLM systems is largely procedural: useful experience is not merely stored information, but reusable procedures for

Hierarchical Multi-Agent Reinforcement Learning for Carbon-Aware AI Data Centers in Power Distribution Systems

arXiv:2607.03324v1 Announce Type: cross Abstract: Eco-friendly energy management for artificial intelligence data centers (AIDCs) is crucial because of the significant increase in energy consumption-i

local-aiarxiv-cs-ai

Memory-Orchestrated Semantic System (MOSS): An Auditable Agentic Memory Architecture

arXiv:2607.04391v1 Announce Type: new Abstract: Long-term memory remains a structural weakness of AI agents. The dominant approach, retrieval-augmented generation (RAG), relies on embedding-based simi

local-aiarxiv-cs-cl

Applications

P^3: Toward Versatile Embodied Agents

arXiv:2508.07033v2 Announce Type: replace Abstract: Embodied agents have shown promising generalization capabilities across diverse physical environments, making them essential for a wide range of rea

applicationsarxiv-cs-ro

SovereignPA-Bench: Evaluating User-Owned Personal Agents under Evolving Intent, Platform Mediation, and Consent Constraints

arXiv:2607.05363v1 Announce Type: new Abstract: Personal agents are becoming persistent user-owned intermediaries: they remember preferences, filter platform-mediated information, use tools, and negot

STAPO: Selective Trajectory-Aware Policy Optimization for LLM Agent Training

arXiv:2607.04963v1 Announce Type: new Abstract: Reinforcement Learning (RL) is the dominant paradigm for training Large Language Model (LLM) agents on long-horizon tasks. However, sparse and delayed r

TACTIC-KG: Toward Small Agent Teams for Cyber Threat Intelligence Knowledge Graph Construction

arXiv:2607.05001v1 Announce Type: cross Abstract: Cyber Threat Intelligence (CTI) reports are predominantly unstructured, heterogeneous, and noisy, which limits their direct usability for automated an

TRACE: Capability-Targeted Agentic Training

arXiv:2604.05336v2 Announce Type: replace Abstract: Models often fail to complete agentic tasks because they lack core capabilities required by the target environment. However, mainstream approaches f

Atomic Task Graph: A Unified Framework for Agentic Planning and Execution

arXiv:2607.01942v1 Announce Type: new Abstract: LLM-based agents have shown strong potential for solving complex multi-step tasks, yet existing performance improvements often rely on either scaling to

BuilderBench: The Building Blocks of Intelligent Agents

arXiv:2510.06288v4 Announce Type: replace Abstract: Today's AI models learn primarily through mimicry and refining, so it is not surprising that they struggle to solve problems beyond the limits set b

Controllable Sim Agents with Behavior Latents

model-releasesarxiv-cs-lg

arXiv:2607.02496v1 Announce Type: cross Abstract: Realistic traffic simulation requires agents that imitate logged behavior and can also be steered along interpretable axes. Such controllability enabl

Criticality-Based Guard Rail Validation for AI Agent Decisions in Autonomous Telecom Networks

arXiv:2607.02210v1 Announce Type: new Abstract: The evolution toward fully autonomous telecommunications networks (Autonomous Network Levels 4-5) requires AI/ML agents to make real-time network decisi

ElephantAgent: Contextual State Continuity in Agentic Systems

arXiv:2607.01919v1 Announce Type: new Abstract: Agentic systems enhance their capabilities by invoking external tools and maintaining persistent memory. However, these external dependencies introduce

Who Gets the Reward & Who Gets the Blame? Evaluation-Aligned Training Signals for Multi-LLM Agents

arXiv:2511.10687v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) in multi-agent systems (MAS) have shown promise for complex tasks, yet current training methods lack principled w

local-aiarxiv-cs-ai

From Personas to Plot: Character-Grounded Multi-Agent Story Generation for Long-Form Narratives

arXiv:2607.00918v1 Announce Type: cross Abstract: Although large language models (LLMs) have demonstrated impressive creative fiction generation, they struggle to maintain narrative consistency and co

2 Jul 2026

PHREEQC-MCQ-200: A Diagnostic Benchmark for Tool-Augmented Scientific Simulator Agents

arXiv:2607.00436v1 Announce Type: new Abstract: Large language model agents are increasingly connected to scientific software, yet it remains unclear when tool access makes scientific computation more

2 Jul 2026

Skills Are Not Islands: Measuring Dependency and Risk in Agent Skill Supply Chains

arXiv:2607.01136v1 Announce Type: cross Abstract: Agent skills package reusable operational knowledge for Large Language Model (LLM) agents, yet as they grow in scope, they become dependency-bearing a

2 Jul 2026

FinPersona-Bench: A Benchmark for Longitudinal Psychometric Stability of Autonomous Financial Agents

arXiv:2606.31522v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous financial agents initialized with explicit behavioral mandates such as 'preserve

Research

LUMOS: A Semantic Operating-System Layer for Accessibility-Grounded AI Agents

arXiv:2606.30697v1 Announce Type: cross Abstract: Current operating systems expose interfaces optimized for human users but not for AI agents. Humans benefit from pixels, icons, windows, visual groupi

researcharxiv-cs-ai

Robust Autonomous UAV Landing on Maritime Platforms via Multimodal Agentic AI and Active Wave Compensation

arXiv:2606.31613v1 Announce Type: new Abstract: Autonomous aerial inspection of marine infrastructure is frequently compromised by stochastic sea states, introducing risks of high-kinetic impacts, pos

agentsarxiv-cs-cv

What Memory Do GUI Agents Really Need? From Passive Records to Active Task-Driving States

model-releasesarxiv-cs-cv

arXiv:2606.31612v1 Announce Type: new Abstract: Mobile GUI agents increasingly face long-horizon tasks that require reading, updating, and reusing task-relevant data across pages and applications. Exi

AutoB2G: Agentic Simulation and Reinforcement Learning for Spatio-Temporal Grid-Interactive Building Control

arXiv:2603.26005v2 Announce Type: replace Abstract: Grid-interactive building control has emerged as a promising approach for improving demand-side flexibility in modern power systems. Realistic studi

Choose Your Agent: Tradeoffs in Adopting AI Advisors, Coaches, and Delegates in Multi-Party Negotiation

arXiv:2602.12089v3 Announce Type: replace-cross Abstract: As AI usage becomes more prevalent in social contexts, understanding agent-user interaction is critical to designing systems that imp rove bot

Collective cooperation without individual fidelity in LLM agents

arXiv:2606.30454v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as agents in simulations of social systems, yet it remains unclear when their behavior can be inter

Complementary RL: Towards Efficient Experience-Driven Agent Learning

arXiv:2603.17621v2 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) has emerged as a powerful paradigm for training LLM-based agents, yet remains limited by low sample efficiency, st

safetyarxiv-cs-cl

Echoes of Human Malice in Agents: Benchmarking LLMs for Multi-Turn Online Harassment Attacks

arXiv:2510.14207v3 Announce Type: replace Abstract: Large Language Model (LLM) agents are powering a growing share of interactive web applications, yet remain vulnerable to misuse and harm. Prior jail

Governance Decay: How Context Compaction Silently Erases Safety Constraints in Long-Horizon LLM Agents

arXiv:2606.22528v2 Announce Type: replace Abstract: Modern LLM agents increasingly rely on context compaction, summarization, or eviction to keep long-running sessions within a token budget. We show t