AI Agent Reliability

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34 papers in the last four weeks, up 240% on the four weeks before. 0.3% of all new papers.

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Latest papers 215

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Nautilus Compass: Black-box Persona Drift Detection for Production LLM Agents
May 11, 2026Chunxiao WangAgent Memory AI Agent Reliability
Yiluo Technology Co., Ltd.
A Communication-Theoretic Framework for LLM Agents: Cost-Aware Adaptive Reliability
May 9, 2026Hamed Omidvar, Vahideh AkhlaghiLLM Inference Efficiency AI Agent Reliability
INTELLERCE LLC San Jose, CA, USA
When Agents Overtrust Environmental Evidence: An Extensible Agentic Framework for Benchmarking Evidence-Grounding Defects in LLM Agents
May 9, 2026Strick Sheng, Ziyue Wang, Liyi ZhouAI Agent Reliability LLM Agent Evaluation
The University of Sydney · Nanjing University
AgentCollabBench: Diagnosing When Good Agents Make Bad Collaborators
May 9, 2026Aritra Mazumder, Shubhashis Roy Dipta, Nusrat Jahan Lia +10AI Agent Reliability Multi-Agent Collaboration
University of Utah · University of Maryland, Baltimore County · University of Dhaka +7
Tool Calling is Linearly Readable and Steerable in Language Models
May 8, 2026Zekun Wu, Ze Wang, Seonglae Cho +4AI Agent Reliability Tool-Augmented Language Model Agents
University College London · Holistic AI · Imperial College London
Beyond the Black Box: Interpretability of Agentic AI Tool Use
May 7, 2026Hariom Tatsat, Ariye ShaterAI Agent Reliability Mechanistic Interpretability
Quantitative Analytics, Barclays
Conformal Agent Error Attribution
May 7, 2026Naihe Feng, Yi Sui, Shiyi Hou +2Agent Failure Analysis AI Agent Reliability
Dalhousie University · Halifax, NS, Canada · Layer 6 AI +1
MANTRA: Synthesizing SMT-Validated Compliance Benchmarks for Tool-Using LLM Agents
May 7, 2026Ashwani Anand, Ivi Chatzi, Ritam Raha +1Computer-Use Agent Benchmarks AI Agent Reliability
Max Planck Institute for Software Systems, Kaiserslautern, Germany
Robust Agent Compensation (RAC): Teaching AI Agents to Compensate
May 5, 2026Srinath Perera, Kaviru Hapuarachchi, Frank Leymann +1AI Agent Reliability LLM Agent Reliability
WSO2 Santa Clara, USA · University of Stuttgart Stuttgart, Germany
ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration
May 4, 2026Ruofeng Yang, Yongcan Li, Shuai LiAI Agent Reliability Multi-Agent LLM Systems
Shanghai Jiao Tong University · Shanghai Innovation Institute
When Alignment Isn't Enough: Response-Path Attacks on LLM Agents
May 4, 2026Mingyu Luo, Zihan Zhang, Zesen Liu +7AI Agent Reliability LLM Agent Security
Fudan University, Shanghai, China · The Hong Kong University of Science and Technology, Hong Kong, China · Huazhong University of Science and Technology, Wuhan, China
Reliable AI Needs to Externalize Implicit Knowledge: A Human-AI Collaboration Perspective
May 3, 2026Hengyu Liu, Tianyi Li, Zhihong Cui +5AI Agent Reliability Human-in-the-Loop AI
Department of Computer Science, Aalborg University, Aalborg, Denmark · Department of Informatics, University of Oslo, Oslo, Norway · School of Computing, Macquarie University, Sydney, Australia
NeuroState-Bench: A Human-Calibrated Benchmark for Commitment Integrity in LLM Agent Profiles
May 3, 2026Xiao JiaAI Agent Reliability LLM Agent Evaluation
School of Artificial Intelligence The Chinese University of Hong Kong, Shenzhen · The Chinese University of Hong Kong, Shenzhen
Reward Hacking Benchmark: Measuring Exploits in LLM Agents with Tool Use
May 3, 2026Kunvar ThamanAI Agent Reliability Reward Hacking
Independent Researcher
Evaluating Agentic AI in the Wild: Failure Modes, Drift Patterns, and a Production Evaluation Framework
May 2, 2026Mukund PandeyAI Agent Reliability AI Agent Evaluation
Independent Researcher
rAIson: Developing Reliable Decision-Making Agents
May 2, 2026Pavlos Moraitis, Nikolaos Spanoudakis, Antonis KakasAI Agent Reliability Explainable Artificial Intelligence
Argument Theory Paris, FR Université Paris Cité Paris, FR · Argument Theory Paris, FR Hellenic Mediterranean University Chania, GR · Argument Theory Paris, FR University of Cyprus Nicosia, CY
TRUST: A Framework for Decentralized AI Service v.0.1
Apr 29, 2026Yu-Chao Huang, Zhen Tan, Mohan Zhang +3AI Agent Reliability AI Accountability
UNITES Lab, University of North Carolina at Chapel Hill · Arizona State University · Columbia University
Operating-Layer Controls for Onchain Language-Model Agents Under Real Capital
Apr 28, 2026T. J. Barton, Chris Constantakis, Patti Hauseman +4AI Agent Reliability LLM Agent Evaluation
DX Research Group (DXRG)
FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments
Apr 28, 2026Amir Saeidi, Venkatesh Mishra, Souradeep Mukhopadhyay +4AI Agent Reliability Multi-Agent LLM Systems
Arizona State University · Cisco Research
GSAR: Typed Grounding for Hallucination Detection and Recovery in Multi-Agent LLMs
Apr 25, 2026Federico A. KamelharAI Agent Reliability Multi-Agent LLM Systems
Senior Principal Architect, Agentic AI Oracle Corporation
Reliable Self-Harm Risk Screening via Adaptive Multi-Agent LLM Systems
Apr 24, 2026Meghana Karnam, Ananya JoshiAI Agent Reliability Multi-Agent LLM Systems
Johns Hopkins University Baltimore, USA
How Consistent Are LLM Agents? Measuring Behavioral Reproducibility in Multi-Step Tool-Calling Pipelines
Apr 23, 2026Abel YagubyanAI Agent Reliability LLM Agent Evaluation
Independent Researcher
CogniConsole: Externalizing Inference-Time Control as a Formal Abstraction for Reliable LLM Interactions
Apr 21, 2026Vanessa Figueiredo, Wilter FranceschiAI Agent Reliability Language Model-Based Control
Orbital Sea Regina, SK, Canada
AI scientists produce results without reasoning scientifically
Apr 20, 2026Martiño Ríos-García, Nawaf Alampara, Chandan Gupta +5AI Agent Reliability Scientific Reasoning
Laboratory of Organic and Macromolecular Chemistry (IOMC), Friedrich Schiller University Jena, Humboldstr. 10, 07743 Jena, Germany · Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India · School of Interdisciplinary Research, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India +3
On the Reliability of Computer Use Agents
Apr 20, 2026Gonzalo Gonzalez-Pumariega, Saaket Agashe, Jiachen Yang +2AI Agent Reliability Agent Reliability
Simular
JTPRO: A Joint Tool-Prompt Reflective Optimization Framework for Language Agents
Apr 20, 2026Sandip Ghoshal, Anshul Mittal, Jyotika Singh +9AI Agent Reliability LLM Tool Use
Oracle AI
SeekerGym: A Benchmark for Reliable Information Seeking
Apr 18, 2026Remy Kim, Minseung Lee, Shuo Li +1AI Agent Reliability Agentic Search
University of Pennsylvania, Curation Labs · Curation Labs · Google DeepMind +1
Evaluating Tool-Using Language Agents: Judge Reliability, Propagation Cascades, and Runtime Mitigation in AgentProp-Bench
Apr 17, 2026Bhaskar GurramAI Agent Reliability Tool-Augmented Language Model Agents
Zasti Inc., Ashburn, VA, USA
Beyond Task Completion: A Verification-vs.-Conformance Gap in Tool-Evolving Agents
Apr 1, 2026Alibek Kaliyev, Artem MaryanskyyAI Agent Reliability Tool-Use Evaluation
The University of Texas at Austin · Austin, Texas, USA · Uber +1
Confident and Wrong: Silent Semantic Failures in Coding Agents
Mar 26, 2026Aman MehtaAI Agent Reliability AI Coding Agents
Snowflake AI Research
MOOSEnger: A Simulation-Aware AI Agent Framework for the MOOSE Ecosystem
Mar 5, 2026Mengnan Li, Jason Miller, Zaid Abulawi +7AI Agent Reliability Agentic Code Generation
Idaho National Laboratory, 995 MK Simpson Blvd, Idaho Falls, 83401, ID, USA
When Agents Disagree With Themselves: Behavioral Consistency as an Uncertainty Signal for LLM Agents
Feb 12, 2026Aman MehtaAI Agent Reliability Selective Prediction
Snowflake AI Research
When Is Enough Not Enough? Illusory Completion in Search Agents
Feb 7, 2026Dayoon Ko, Jihyuk Kim, Sohyeon Kim +5AI Agent Reliability LLM Answer Verification
Seoul National University · LG AI Research · University of Illinois Chicago
AgentRx: Diagnosing AI Agent Failures from Execution Trajectories
Feb 2, 2026Shraddha Barke, Arnav Goyal, Alind Khare +3Agent Failure Analysis AI Agent Reliability
1Microsoft Research · 2Microsoft · 3UIUC
Replayable Financial Agents: A Determinism-Faithfulness Assurance Harness for Tool-Using LLM Agents
Jan 17, 2026Raffi KhatchadourianAI Agent Reliability LLM Agent Evaluation
IBM Financial Services Market, New York, NY, USA

May 11, 2026, cs.CRJ/K move · Enter open · S save

Nautilus Compass: Black-box Persona Drift Detection for Production LLM Agents

Chunxiao Wang

Yiluo Technology Co., Ltd.

Agent Memory AI Agent Reliability AI Coding Agents Persona Consistency LLM Agent Reliability

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Production LLM coding agents drift over long sessions: they forget user-specified constraints, slip into mistakes the user already flagged, and confabulate prior agreements. White-box approaches such as persona vectors require model weights and so cannot be applied to closed APIs (Claude, GPT-4) that most users actually interact with. We present Nautilus Compass, a black-box persona drift detector and agent memory layer for production coding agents. The method operates entirely at the prompt-text layer: cosine similarity between user prompts and behavioral anchor texts, aggregated by a weighted top-k mean using BGE-m3 embeddings. Compass is, to our knowledge, the only public agent memory layer (among Mem0, Letta, Cognee, Zep, MemOS, smrti verified May 2026) that does not call an LLM at index time to extract facts or build a graph; raw conversation text is embedded directly. The system ships as a Claude Code plugin, an MCP 2024-11-05 A2A server (Cursor, Cline, Hermes), a CLI, and a REST API on one daemon, with a Merkle-chained audit log for tamper-evident anchor updates. On a held-out test set built from real Claude Code session traces and labeled by an independent LLM judge, Compass reaches ROC AUC 0.83 for drift detection. The embedded retrieval pipeline scores 56.6% on LongMemEval-S v0.8 and 44.4% on EverMemBench-Dynamic (n=500), topping the four published EverMemBench Table 4 baselines. LongMemEval-S 56.6% is ~30 points below recent white-box leaders (90+%); we treat that as the architectural ceiling of the no-extraction design. End-to-end reproduction cost is $3.50 (~14x cheaper than GPT-4o-judged stacks). A paired cross-vendor behavior A/B accompanies these numbers as preliminary system-level evidence. Code, anchors, frozen test data, and audit-log tooling are MIT-licensed at github.com/chunxiaoxx/nautilus-compass.

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