Search: “mcp”

AgentTrap: Stateful Feedback Deception against Autonomous Penetration Testing Agents

arXiv:2610.02869v1 Announce Type: cross Abstract: Autonomous penetration testing agents conduct multi-step attacks by continuously adapting their plans and actions to target responses. As a common def

5 Oct 2026

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Evaluating and Improving the Robustness of Large Language Models to Input Sequence Variations

DGX agent

arXiv:2610.02432v1 Announce Type: cross Abstract: Large language models (LLMs) in production systems face prompt injections, trojans (backdoors), and manipulation of automatic quality metrics. This th

model-releasesarxiv-cs-cl

5 Oct 2026

LPS-Bench: Benchmarking Safety Awareness of Computer-Use Agents in Long-Horizon Planning under Benign and Adversarial Scenarios

arXiv:2602.03255v2 Announce Type: replace Abstract: Computer-use agents (CUAs) execute multi-stage tasks through tools, where an early unsafe decision can propagate to consequential actions. Evaluatin

5 Oct 2026

Toward SLM-based agentic task-tool intent matching

arXiv:2610.03213v1 Announce Type: new Abstract: Tool-equipped AI agents use tool calls to access data and act on external systems. Horizontal growth of agentic systems increases the number of these in

5 Oct 2026

Finding the Right Fit: Model-Harness Interactions across Agent Tasks

arXiv:2610.00917v1 Announce Type: new Abstract: Choosing an agent system means choosing both a language model and the harness through which it acts. We ask whether a strong model, harness, or pairing

Measuring the Microtask Eligibility Gap: When Is an Off-the-Shelf SLM Enough for an Agent Harness?

arXiv:2610.00025v1 Announce Type: new Abstract: Agent harnesses increasingly want to run small language models (SLMs) on the microtasks around a frontier large language model (LLM) planner: auto-appro

Tokenized Key-Gated Adapter Routing: A Secure Access Control Mechanism Against Private Data Leakage in LLMs

arXiv:2610.00309v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in privacy-critical domains (e.g., healthcare, finance, and government), but their propensity t

Safety

YouRA: A Persistent-State Architecture for Evidence-Traceable Autonomous Research Agents

arXiv:2610.01097v1 Announce Type: new Abstract: End-to-end research agents can now produce complete scientific papers, yet manuscript claims often diverge from executed experiments. This gap is struct

safetyarxiv-cs-ai

Janus: Evidence-Before-Effect Sagas and Offline-Verifiable Provenance for Agentic LLMs

arXiv:2609.38266v1 Announce Type: cross Abstract: Agentic large language models (LLMs) now move money through tools, yet the record of what they did is usually a trace their own process emits beside t

1 Oct 2026

Mid-Harness: Scaling Actions Between Model and Harness for Terminal Agents

arXiv:2609.39982v1 Announce Type: cross Abstract: Terminal agents act through stochastic model generations, yet the ability to generate a useful action does not ensure its reliable execution. A poor c

1 Oct 2026

SkillSeek: Revisiting Agent Skill Retrieval at Marketplace Scale

arXiv:2609.38822v1 Announce Type: cross Abstract: Anthropic's Agent Skills package reusable procedural know-how for an LLM agent into SKILL.md directories, and open-source aggregations have grown past

1 Oct 2026

Auditable Long-Term Memory: A Deterministic Retrieval Chain Measured at 479/475 of 500 on LongMemEval-S

arXiv:2609.38021v1 Announce Type: cross Abstract: We evaluate an auditable long-term memory system on LongMemEval-S. Its retrieval chain uses hybrid candidate retrieval, cross-encoder reranking, cover

30 Sept 2026

Beyond Approved Actions: Runtime Validation of Persistent Outcomes in Agent Workflows

arXiv:2609.31301v1 Announce Type: cross Abstract: Large language model agents increasingly act on software systems, no longer merely generating text but also changing databases and online services. Ho

28 Sept 2026

MOOSEnger: A Simulation-Aware AI Agent Framework for the MOOSE Ecosystem

arXiv:2603.04756v3 Announce Type: replace Abstract: MOOSEnger is a modeling and simulation AI agent framework for the Multiphysics Object-Oriented Simulation Environment (MOOSE) ecosystem, built aroun

25 Sept 2026

Persistent Billable State: Denial-of-Wallet Attacks and Defenses in Tool-Calling LLM Agents

arXiv:2609.28585v1 Announce Type: cross Abstract: Multi-step tool-calling LLM agents rely on host runtimes to preserve state across turns. When a runtime carries an external tool return into later mod

25 Sept 2026

Progressive Skill Discovery as Access Control for Tool-Using LLM Agents: Structural Governance through Role-Scoped Capability Delivery

arXiv:2609.28693v1 Announce Type: new Abstract: Large Language Model (LLM) agents struggle to scale safely when exposed to vast enterprise toolsets. Providing an agent with access to every internal to

25 Sept 2026

State-Grounded Conditioning: Wrapping User-Facing LLM Agents Where Direction Depends on Live State

arXiv:2609.27606v1 Announce Type: new Abstract: We introduce State-Grounded Conditioning (SGC), a design principle for user-facing LLM agents that must condition on live user state (game state, sessio

24 Sept 2026

PhysAI-Bench: A Benchmark for LLM-Based Agentic Decision-Making in Autonomous UAV-Centric Physical AI

arXiv:2609.23695v1 Announce Type: new Abstract: Recent advances in Physical AI have accelerated the use of foundation models in autonomous systems such as unmanned aerial vehicles (UAVs), which must p

23 Sept 2026

ToolCUA: Towards Optimal GUI-Tool Path Orchestration for Computer Use Agents

arXiv:2605.12481v2 Announce Type: replace Abstract: Computer Use Agents (CUAs) can act through both atomic GUI actions, such as click and type, and high-level tool calls, such as API-based file operat

23 Sept 2026

Closed-World Resolution Against Tool Hallucination in LLM Agents

arXiv:2609.19425v1 Announce Type: new Abstract: Tool-augmented large language model (LLM) agents fail in a way no tool-selection or tool-security method addresses: they call tools that do not exist an

18 Sept 2026

Safety

Position: It is Time to Virtualize Foundation Models with a Self-evolving Operating System Layer

arXiv:2609.19203v1 Announce Type: new Abstract: AI applications have shifted from single, monolithic foundation models (FM) to compound agentic systems. Yet today's stacks remain fragmented: even as p

safetyarxiv-cs-ai

18 Sept 2026

Market Signal Injection: Adversarial Context Manipulation of LLM Pricing Agents

arXiv:2609.18357v1 Announce Type: new Abstract: Large language model (LLM) pricing agents may respond to how market data is presented, even when its numerical values remain unchanged. We introduce mar

17 Sept 2026

TuiML: Machine Learning for AI Agents

arXiv:2609.17984v1 Announce Type: new Abstract: Machine-learning libraries such as Weka and scikit-learn were designed for human programmers. Language-model agents now use these same libraries by reca

17 Sept 2026

A Framework for Generating Valid Context-Specific Benchmarks through Expert Guidance

arXiv:2609.16592v1 Announce Type: new Abstract: This paper presents an end-to-end approach for generating context-specific large language model (LLM) benchmark datasets by combining expert input with

EchoPath: Execution-Level Replayable Memory for GUI Agents

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

RegNetAgents: A Multi-Agent Framework for Cross-Network Regulatory Driver Identification in Cancer Genomics

arXiv:2607.14097v2 Announce Type: replace Abstract: We introduce RegNetAgents, an AI-oriented multi-agent framework for structured, query-driven regulatory candidate identification across heterogeneou

Shared Selective Persistent Memory for Agentic LLM Systems

arXiv:2607.09493v2 Announce Type: replace Abstract: Agentic LLM systems that generate code through multi-turn tool use face a fundamental context problem: each session starts from zero, discarding the

ActGuard: Pre-execution Action Auditing against Indirect Prompt Injection in LLM Agents

arXiv:2609.14987v1 Announce Type: cross Abstract: Large language model (LLM) agents interact with external environments through tool invocation, but tool outputs can also expose them to indirect promp

AutoTailor: Automatic, User-Aligned Capability Selection and Adaptation for Web Agents

arXiv:2609.13548v1 Announce Type: new Abstract: Web agents can utilize reusable tools to reduce the cost and latency of low-level browser interaction, but automatically discovered tool collections can

Confuse the Model, Control the Flow: Understanding and Mitigating Privacy Leakage from LLM Agents with Information Flow Control

arXiv:2609.14003v1 Announce Type: cross Abstract: Personal AI agents built on large language models (LLMs) are increasingly given access to a user's private data and communications in order to provide

EvoOntology: A Self-Evolving Ontology Layer for Data Agents

arXiv:2609.15779v1 Announce Type: new Abstract: Data agents aim to fulfill natural-language instructions over heterogeneous data, including tables, files, and databases. However, data agents face a ch

Solar Intelligence

arXiv:2609.13648v1 Announce Type: new Abstract: Solar energy decision support is fragmented across dashboards that provide data without explanation, research papers are slow to parse, and general-purp

Turkish MMLU Pro: Traceable Option Augmentation and Its Validity Limits in Turkish Multiple-Choice Evaluation

arXiv:2609.15467v1 Announce Type: cross Abstract: Adding answer options can lower multiple-choice scores without improving assessment validity. Turkish MMLU Pro examines this distinction using 12,000

When Tool Calls Succeed but Workflows Fail: Anomalies at the Agent-Tool Boundary

arXiv:2609.15397v1 Announce Type: new Abstract: AI agents increasingly execute long-running workflows that externalize effects through independently supplied tools. Under retries, speculative executio

An Agentic Evaluation Framework for AI-Generated Scientific Code in PETSc

arXiv:2603.15976v2 Announce Type: replace Abstract: While LLMs have accelerated scientific code generation, comprehensively evaluating generated code remains challenging. Many benchmarks emphasize fun

12 Sept 2026

Generating a Consistent Enterprise: Synthesis and Reference-Free Evaluation of Multi-System Business Data

arXiv:2609.11286v1 Announce Type: new Abstract: Synthetic relational data is normally produced by a model trained on a real dataset, and its quality is measured as the distance to that dataset. This p

12 Sept 2026

Overview of the NLPCC 2026 Shared Task 11: Agent-Based Experiment Reproduction from Scientific Papers

model-releasesarxiv-cs-cl

arXiv:2609.11117v1 Announce Type: new Abstract: Reproducibility is essential to scientific progress, yet the growing volume and complexity of scientific publications make exhaustive manual verificatio

11 Sept 2026

Safety

AgentBrew: Offline Tool-Use Agent Learning from Raw Real-World Trajectories

arXiv:2609.05837v1 Announce Type: new Abstract: LLM-based agents are increasingly deployed in real-world applications through tool-use APIs, yet training them for specific environments remains fundame

safetyarxiv-cs-ai

10 Sept 2026

Agentic AI-enabled Semantic Commissioning of a Cognitive Digital Twin for Reconfigurable Manufacturing

arXiv:2609.09503v1 Announce Type: new Abstract: Rapid bespoke commissioning of the Cognitive Digital Twin (CDT) is a major challenge in reconfigurable manufacturing. Traditional digital twin (DT) cons

agentsarxiv-cs-ro

10 Sept 2026

ResidualAuth: What Authorization State Must Language Agents Preserve under Revocable Delegation?

arXiv:2609.08062v1 Announce Type: new Abstract: Tool-using language agents can delegate and revoke permissions while acting through external services. We show that two authorization histories can have

10 Sept 2026

3DHarnessBench: Probing Agentic 3D-to-Code Capabilities of Frontier Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.06535v1 Announce Type: new Abstract: We introduce 3DHarnessBench, a benchmark that evaluates the agentic ability of frontier vision-language models (VLMs) to recover 3D geometry as Blender

How Long Until Your Robot Ignores You? A Safety Benchmark for LLM Orchestrators in Human-Humanoid Collaboration

model-releasesarxiv-cs-ro

arXiv:2609.07288v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly employed to orchestrate robot behavior through natural-language interfaces, yet no benchmark exists to eva

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments?

model-releasesarxiv-cs-cv

arXiv:2412.09529v4 Announce Type: replace Abstract: Radiology, with its heterogeneous modalities, anatomies, and evolving protocols, is a natural yet high-stakes testbed for agentic AI. As LLMs grow m

Poisson Image Denoising Using Minimax Concave and Reweighted ell_1 Penalties: Nonblind and Blind Approaches

arXiv:2609.07916v1 Announce Type: new Abstract: Images are important tools in various sciences. Despite the development of photo-taking tools, creating clear and image without noise remains challengin

agentsarxiv-cs-cv

CUA-Universe: A Scalable and Dynamic Environment for Hybrid GUI+CLI Agents

arXiv:2609.05374v1 Announce Type: new Abstract: Computer-use agents have advanced on benchmarks like OSWorld and AndroidWorld, but still act mostly through the GUI, often producing inefficient traject

7 Sept 2026

Local Ai

The Natural Language Interaction Protocol and Standard for AI Agents

arXiv:2609.04135v1 Announce Type: new Abstract: AI agents are increasingly being developed and deployed across organizations using heterogeneous agent-development frameworks, AI models, tool interface

local-aiarxiv-cs-ai

4 Sept 2026

A Hybrid Insider Threat Detection Framework Combining Multi-Agent Simulation, Layered SIEM Correlation, and Theory-of-Mind Reasoning

arXiv:2601.04243v2 Announce Type: replace-cross Abstract: This paper presents a hybrid insider threat detection framework for enterprise environments, integrating multi-agent simulation, layered SIEM

2 Sept 2026

Delegation Without Trust: An Empirical Gap Analysis of Identity, Authorization, and Runtime Governance in Multi-Agent LLM Systems

arXiv:2609.00267v1 Announce Type: cross Abstract: Autonomous LLM agents increasingly act on a user's behalf: they hold credentials, call tools and services, and spawn sub-agents that act further on th