Search: “agents”

Context-Fractured Decomposition Attacks on Tool-Using LLM Agents: Exploiting Artifact Provenance Gaps

arXiv:2606.09084v1 Announce Type: cross Abstract: Tool-using LLM agents interact with the world through actions that persist state in artifacts (e.g., workspace files or logs). Consequently, jailbreak

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Agents

Cost-Aware Speculative Execution for LLM-Agent Workflows: An Integrated Five-Dimension Method

DGX agent

arXiv:2606.07846v1 Announce Type: cross Abstract: LLM-agent workflows chain model calls and tool invocations, and spend most of their wall-clock time waiting on upstream operations before downstream o

agentsarxiv-cs-ai

9 Jun 2026

MBABench: Evaluating LLM Agents on End-to-End Spreadsheet Tasks in Finance

arXiv:2605.22664v2 Announce Type: replace Abstract: LLM agents are increasingly expected to carry out end-to-end workflows, producing complete artifacts from high-level user instructions. To meet ente

Oversight Has a Capacity: Calibrating Agent Guards to a Subjective, Fatiguing Human

arXiv:2606.08919v1 Announce Type: new Abstract: As LLM agents begin to take real, irreversible actions (shell commands, file edits, deploys), the standard safety pattern is a human-in-the-loop approva

POISE: Position-Aware Undetectable Skill Injection on LLM Agents

arXiv:2606.07943v1 Announce Type: cross Abstract: Agent skills provide a lightweight mechanism for extending general-purpose agents, but their open format exposes them to skill-poisoning attacks. A pr

REFLECT: Intervention-Supported Error Attribution for Silent Failures in LLM Agent Traces

arXiv:2606.09071v1 Announce Type: new Abstract: Large language model (LLM) agents now solve complex tasks through long plan-and-execution traces, yet the ability to locate errors in a completed traces

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection

arXiv:2606.08146v1 Announce Type: new Abstract: Fraud detection in payment, e-commerce, and telecommunications systems requires accuracy at the individual level, robustness under severe class imbalanc

WeaveBench: A Long-Horizon, Real-World Benchmark for Computer-Use Agents with Hybrid Interfaces

arXiv:2606.09426v1 Announce Type: new Abstract: Computer-use agents (CUAs) increasingly operate in runtimes that combine visual desktop control, command-line execution, code editing, browsers, and ext

Do Coding Agents Deceive Us? Detecting and Preventing Cheating via Capped Evaluation with Randomized Tests

arXiv:2606.07379v1 Announce Type: cross Abstract: A growing failure mode in agent evaluation and training is that models can achieve high evaluation scores by exploiting shortcuts instead of solving t

LLM Agent-Assisted Reverse Engineering with Quantitative Readability Metrics

arXiv:2606.06838v1 Announce Type: cross Abstract: Automatic decompilers produce functionally correct but often unreadable C code. This paper addresses one stage of the reverse engineering workflow: im

Local Ai

Queen-Bee Agents: A BeeSpec-Centered Architecture for Governed Enterprise MCP Orchestration

arXiv:2606.06545v1 Announce Type: cross Abstract: Enterprise agent systems increasingly need to connect large language models to private tools, internal knowledge, and Model Context Protocol (MCP) int

local-aiarxiv-cs-ai

SCALE: Scalable Cross-Attention Learning with Extrapolation for Agentic Workflow Scheduling

arXiv:2606.06820v1 Announce Type: cross Abstract: Agentic Large Language Model (LLM) systems decompose complex tasks into workflow Directed Acyclic Graphs (DAGs) whose primitives must be scheduled on

Adversarial Agents: Black-Box Evasion Attacks with Reinforcement Learning

arXiv:2503.01734v3 Announce Type: replace-cross Abstract: Attacks on machine learning models have been extensively studied through stateless optimization. In this paper, we demonstrate how a reinforce

Memory is Reconstructed, Not Retrieved: Graph Memory for LLM Agents

arXiv:2606.06036v1 Announce Type: new Abstract: Despite recent progress, LLM agents still struggle with reasoning over long interaction histories. While current memory-augmented agents rely on a stati

Search-Time Contamination in Deep Research Agents: Measuring Performance Inflation in Public Benchmark Evaluation

arXiv:2606.05241v1 Announce Type: cross Abstract: Public benchmarks enable fair and reproducible evaluation of LLM reasoning, but they become fragile for deep research agents that actively search the

The End of Software Engineering: How AI Agents Are Fundamentally Restructuring the Software Paradigm

arXiv:2606.05608v1 Announce Type: cross Abstract: For over half a century, software engineering has operated on a foundational premise: human engineers decompose problems, encode decision logic into s

Towards Healthy Evolution: Exploring the Role and Mechanisms of Human-Agent Interaction in Self-Evolving Systems

arXiv:2606.06114v1 Announce Type: new Abstract: Self-evolving agents improve through continual self-play and self-generated learning signals, but autonomous evolution can also cause capability degrada

EGTR-Review: Efficient Evidence-Grounded Scientific Peer Review Generation via Multi-Agent Teacher Distillation

arXiv:2606.06025v1 Announce Type: new Abstract: Scientific peer review generation has attracted increasing attention for reducing reviewing burdens and providing timely feedback. However, existing Lar

Harnessing Generalist Agents for Contextualized Time Series

arXiv:2606.05404v1 Announce Type: cross Abstract: Time series are often embedded in rich contexts that are essential for holistic modeling. Moreover, real-world practitioners often require end-to-end

Humans' ALMANAC: A Human Collaboration Dataset of Action-Level Mental Model Annotations for Agent Collaboration

arXiv:2606.06388v1 Announce Type: cross Abstract: Recent advances in LLM agents have enabled complex cognitive capabilities, such as multi-step reasoning, planning, and tool use, that increasingly pos

TensorBench: Benchmarking Coding Agents on a Compiler-Based Tensor Framework

arXiv:2606.05570v1 Announce Type: new Abstract: Repository-level coding benchmarks face a trade-off between task difficulty and evaluation reliability: tasks that challenge frontier models often invol

Be Fair! Can Machine Learning Engineering Agents Adhere to Fairness Constraints?

arXiv:2606.04971v1 Announce Type: new Abstract: Machine learning engineering (MLE) agents promise to automate end-to-end ML pipeline development from raw data and natural language instructions, potent

safetyarxiv-cs-lg

DAR: Deontic Reasoning with Agentic Harnesses

arXiv:2606.05009v1 Announce Type: cross Abstract: Deontic reasoning is the task of answering questions by applying explicit rules and policies to case-specific facts, for example computing tax liabili

Fog of Love: Engineering Virtuous Agent Behavior with Affinity-based Reinforcement Learning in a Game Environment

arXiv:2606.04750v1 Announce Type: new Abstract: Instilling virtuous behavior in artificial intelligence has seen increasing interest. One of the techniques proposed is known as affinity-based reinforc

Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

arXiv:2507.21892v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) mitigates hallucination in LLMs by incorporating external knowledge, but relies on chunk-based retrieval that l

Learning While Acting: A Skill-Enhanced Test-Time Co-Evolution Framework for Online Lifelong Learning Agents

arXiv:2606.04815v1 Announce Type: cross Abstract: Lifelong learning is essential for Large Language Model (LLM) agents operating in dynamic, interactive environments. However, existing lifelong learni

Optimizing the Cost-Quality Tradeoff of Agentic Theorem Provers in Lean

arXiv:2606.04883v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in workflows for generating formal proofs in Lean. These workflows often decompose problems into smal

Agentic Chain-of-Thought Steering for Efficient and Controllable LLM Reasoning

arXiv:2606.03965v1 Announce Type: cross Abstract: Large language models improve final-answer accuracy through extended chain-of-thought reasoning, but often spend tokens inefficiently and offer little

DELTAMEM: Incremental Experience Memory for LLM Agents via Residual Trees

arXiv:2606.03083v1 Announce Type: new Abstract: Large Language Model (LLM)-based agents increasingly rely on memory to learn from experiences over continual interactions. However, storing experiences

Local Ai

InfoMem: Training Long-Context Memory Agents with Answer-Conditioned Information Gain

arXiv:2606.03329v1 Announce Type: new Abstract: Long-context tasks require LLMs to identify and preserve answer-relevant information from large contexts. Chunk-wise memory agents address this issue by

local-aiarxiv-cs-ai

MedCUA-Bench: A Screenshot-Only Benchmark for Clinical Computer-Use Agents

arXiv:2606.03203v1 Announce Type: new Abstract: Computer-use agents could automate repetitive screen-based clinical work, but their reliability in medical graphical user interfaces remains largely unv

PhotoCraft: Agentic Reasoning with Hierarchical Self-Evolving Memory for Deep Image Search

arXiv:2606.03099v1 Announce Type: cross Abstract: Deep Image Search requires multi-step reasoning over rich contextual cues, such as time, location, and event relations. However, most existing LLM-bas

The Impact of Configuring Agentic AI Coding Tools on Build-vs-Buy Decisions: A Study Protocol

arXiv:2606.03907v1 Announce Type: cross Abstract: Agentic AI coding tools write code with increasing autonomy and in doing so decide when to import a library and when to implement functionality from s

The Ringelmann Effect in Multi-Agent LLM Systems: A Scaling Law for Effective Team Size

arXiv:2606.02646v1 Announce Type: cross Abstract: Inference-time multi-agent LLM scaling lacks a shared unit: counting nominal agents conflates cost with independent evidence. We derive a two-paramete

Think-Before-Speak: From Internal Evaluation to Public Expression in Multi-Agent Social Simulation

arXiv:2606.03137v1 Announce Type: new Abstract: LLM-based multi-agent simulation offers a promising way to study social interaction, deliberation, and collective opinion dynamics. However, many existi

Local Ai

Toward a Modular Architecture for Embedded AI Agent Systems at the Edge

arXiv:2606.02862v1 Announce Type: new Abstract: The rise of Large Language Models (LLMs) has enabled agentic AI capable of complex reasoning and tool use; however, deploying such autonomy in pervasive

local-aiarxiv-cs-ai

What Makes Interaction Trajectories Effective for Training Terminal Agents?

arXiv:2606.03461v1 Announce Type: new Abstract: Stronger code agents are commonly assumed to be superior teachers for post-training, yet this assumption remains poorly disentangled from task difficult

A Multi-AI-agent Framework Enabling End-to-end Finite Element Analysis for Solid Mechanics Problems

arXiv:2606.00138v1 Announce Type: new Abstract: Finite element analysis (FEA) is the most important numerical approach for solid mechanics. Challenges of FEA include a steep learning curve for entry-l

ACON: Optimizing Context Compression for Long-horizon LLM Agents

arXiv:2510.00615v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as agents in dynamic real-world environments, where success depends on maintaining precise re

Adversarial Feeds Steer LLM Agent Decisions Against Their Defaults

arXiv:2606.00914v1 Announce Type: new Abstract: LLM agents increasingly act after consuming ranked external information streams such as social feeds, search results, retrieval contexts, and email queu

AGENTCL: Toward Rigorous Evaluation of Continual Learning in Language Agents

arXiv:2606.02461v1 Announce Type: new Abstract: Language agents spend substantial inference time solving individual tasks, yet the experience acquired in one episode is often underutilized in future e

AMP: A Vendor-Neutral Wire Format for Agent Memory Operations

arXiv:2606.01138v1 Announce Type: cross Abstract: Agent-memory frameworks - mem0, Letta/MemGPT, Cognee, Zep/Graphiti, MemoryOS, MemTensor - each ship their own SDK, storage layout, and operational voc

ASE-26: a curriculum for agentic software engineering as a discipline

arXiv:2606.01152v1 Announce Type: cross Abstract: The work of a professional software engineer has begun to consist, increasingly, of directing agents rather than writing code, and the empirical evide

Benchmarking Security Risk Detection and Verification in Open Agentic Skill Ecosystems

arXiv:2606.00925v1 Announce Type: cross Abstract: Open agent platforms allow community contributors to publish reusable skills that agents can invoke at runtime. This extensibility also creates a supp

Characterization of Multi-Model Agentic AI Systems on General Tasks via Trace-Driven Simulation

arXiv:2606.01725v1 Announce Type: new Abstract: Agentic AI completes tasks through iterative planning, tool use, and reasoning based on observed outcomes. Despite its popularity, its system-level beha

Coordinating Task Switching in a Robotics Multi-Agent System Using Behavior Trees

arXiv:2606.01170v1 Announce Type: cross Abstract: The application of multi-agent systems in robotics is a very challenging field. Several competitions involving such systems are proposed to foster res

agentsarxiv-cs-ro

CRAB-Bench: Evaluating LLM Agents under Complex Task Dependencies and Human-aligned User Simulation

arXiv:2606.01815v1 Announce Type: new Abstract: Evaluating LLM agents in realistic service scenarios requires complex task dependencies, imperfect user behavior, and an evaluation that accommodates mu

'I Strongly Suspect This Website Is a Scam': Benchmarking PII Leakage and Detection without Defense in Autonomous Web Agents

arXiv:2606.00497v1 Announce Type: cross Abstract: Deceptive web content, widely instantiated across the internet and commonly known as extit{social-engineering attacks}, manipulates autonomous web age