LLM Reliability

LLM: Large Language Model

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Overview

It asks not only whether a model gets an answer right, but whether it knows when it may be wrong, follows constraints, uses evidence faithfully, and behaves consistently across repeated or multi-turn use. Researchers test these properties with adversarial and perturbation benchmarks, repeated-run and cross-language evaluations, domain-specific tasks, and audits of LLM judges and tool-using agents. Common approaches include estimating uncertainty from logits, hidden representations, or response agreement; selective abstention and conformal calibration; retrieval and symbolic verification; and training methods that reward grounded answers, correction, or hesitation. The central tension is that benchmark accuracy and verbal confidence often fail to predict reliability on individual cases, long tasks, or shifted inputs, while stronger checks and abstention trade coverage, latency, and cost for safer decisions.

Latest papers

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802 papers116 papers in the last four weeks, up 18% on the four weeks before. 0.7% of all new papers.

  1. Beyond Scalars: Evaluating and Understanding LLM Reasoning via Geometric Progress and Stability

    Mar 11, 2026Xinyan Jiang, Ninghao Liu, Di Wang +1LLM ReliabilityLLM Reasoning

    Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) · King Abdullah University of Science and Technology · Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China +2

  2. Evaluating Reliability Gaps in Large Language Model Safety via Repeated Prompt Sampling

    Mar 10, 2026Keita BroadwaterLLM EvaluationLanguage Model Safety Evaluation

    Independent Researcher, San Jose, USA

  3. Why LLMs Fail: A Failure Analysis and Partial Success Measurement for Automated Security Patch Generation

    Mar 10, 2026Amir Al-MaamariAutomated Program RepairSoftware Security

    University of Passau, Germany

  4. Collective AI can amplify tiny perturbations into divergent decisions

    Mar 10, 2026Hajime Shimao, Warut Khern-am-nuai, Sung Joo KimLLM Decision-MakingMulti-Agent LLMs

    The Pennsylvania State University, Malvern, PA, USA · McGill University, Montreal, QC, Canada · American University, Washington, DC, USA

  5. Can LLMs Perceive Time? An Empirical Investigation

    Mar 9, 2026Aniketh GarikaparthiTemporal Reasoning in Language ModelsLLM Inference

    TCS Research

  6. Evaluating Financial Intelligence in Large Language Models: Benchmarking SuperInvesting AI with LLM Engines

    Mar 9, 2026Akshay Gulati, Kanha Singhania, Tushar Banga +8Financial Reasoning in Language ModelsFinancial Reasoning Benchmarks

    The Future University

  7. Tabular PDF Information Extraction with Local LLMs and Layout-Aware Parsing: A Reliability Evaluation

    Mar 9, 2026Muhammad Anis Al Hilmi, Neelansh Khare, Noel Framil Iglesias +3Document Information ExtractionDocument Parsing

    Informatics, Faculty of Engineering, Universitas Swadaya Gunung Jati, Cirebon, Indonesia · Computer Science, University of California, Irvine, USA · Computer Engineering, UNIR, La Rioja, Spain +1

  8. Benchmarking Large Language Models for Quebec Insurance: From Closed-Book to Retrieval-Augmented Generation

    Mar 8, 2026David Beauchemin, Richard KhouryLLM EvaluationLLM Reliability

    Group for Research in Artificial Intelligence of Laval University (GRAIL), Université Laval, Quebec City, Quebec, Canada

  9. Toward Epistemic Stability: Engineering Consistent Procedures for Industrial LLM Hallucination Reduction

    Mar 8, 2026Brian Freeman, Adam Kicklighter, Matt Erdman +1LLM Hallucination MitigationLLM Prompting

    Trane Technologies, Davidson NC, USA

  10. Optimizing LLM Annotation of Classroom Discourse through Multi-Agent Orchestration

    Mar 8, 2026Bakhtawar Ahtisham, Kirk Vanacore, Rene F. KizilcecLLM-Assisted AnnotationAI in Education

    Cornell University, USA

  11. Did You Forget What I Asked? Prospective Memory Failures in Large Language Models

    Mar 7, 2026Avni MittalInstruction FollowingLLM Reliability

  12. Validation of a Small Language Model for DSM-5 Substance Category Classification in Child Welfare Records

    Mar 6, 2026Brian E. Perron, Dragan Stoll, Bryan G. Victor +3ClassificationSmall Language Models

    School of Social Work, University of Michigan · Institute of Psychology and Education, Ulm University, Germany · School of Social Work, ZHAW Zurich University of Applied Sciences, Switzerland +1

  13. Agentic retrieval-augmented reasoning reshapes collective reliability under model variability in radiology question answering

    Mar 6, 2026Mina Farajiamiri, Jeta Sopa, Saba Afza +9LLM ReliabilityLLM Agent Reliability

    Lab for AI in Medicine, RWTH Aachen University, Aachen, Germany. · Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany. · Department of Diagnostic and Interventional Radiology, TUM University Klinikum, School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany. +6

  14. Verify to Amplify: Improving Reasoning via Learned Chain-of-Thought Verification

    Mar 3, 2026Maria-Florina Balcan, Avrim Blum, Kiriaki Fragkia +2LLM EvaluationLLM Answer Verification

    Carnegie Mellon University · Toyota Technological Institute at Chicago · Northwestern University

  15. When Shallow Wins: Silent Failures and the Depth-Accuracy Paradox in Latent Reasoning

    Mar 3, 2026Subramanyam Sahoo, Aman Chadha, Vinija Jain +1LLM Mathematical ReasoningReasoning Consistency in Language Models

    Independent · AWS Generative AI Innovation Center, Amazon Web Services · Stanford University +2

  16. Evaluating Performance Drift from Model Switching in Multi-Turn LLM Systems

    Mar 3, 2026Raad Khraishi, Iman Zafar, Katie Myles +1LLM ReliabilityMulti-Turn Dialogue Evaluation

    NatWest AI Research · University College London

  17. TrustMH-Bench: A Comprehensive Benchmark for Evaluating the Trustworthiness of Large Language Models in Mental Health

    Mar 3, 2026Zixin Xiong, Ziteng Wang, Haotian Fan +2LLM Safety BenchmarksLLM Reliability

    Renmin University of China, China · Beijing University of Posts and Telecommunications, China · Hefei University of Technology, China

  18. Probing Materials Knowledge in LLMs: From Latent Embeddings to Reliable Predictions

    Mar 2, 2026Vineeth Venugopal, Soroush Mahjoubi, Elsa OlivettiLLM ReliabilityLLM Evaluation

    Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA.

  19. RubricBench: Aligning Model-Generated Rubrics with Human Standards

    Mar 2, 2026Qiyuan Zhang, Junyi Zhou, Yufei Wang +8LLM EvaluationRubric-Based Evaluation

    City University of Hong Kong · Tencent Hunyuan · McGill - Mila & Quebec AI Institute +2

  20. Quantifying Conversational Reliability of Large Language Models under Multi-Turn Interaction

    Mar 2, 2026Jiyoon MyungTool Selection for Language Model AgentsLLM Reliability

    Samsung SDS

  21. PARCER as an Operational Contract to Reduce Variance, Cost, and Risk in LLM Systems

    Mar 1, 2026Elzo Brito dos Santos FilhoContext EngineeringLLM Reliability

  22. Are LLMs Reliable Code Reviewers? Systematic Overcorrection in Requirement Conformance Judgement

    Feb 28, 2026Haolin Jin, Huaming ChenAutomated Code ReviewLLM Reliability

    University of Sydney, Sydney, NSW, Australia.

  23. LLMs Remember First, Forget Last: Dual-Process Interference in Large Language Models

    Feb 27, 2026Sourav Chattaraj, Kanak RajLLM ReliabilityBelief Updating in LLMs

    Thomson Reuters, Bengaluru, India

  24. Mitigating Legibility Tax with Decoupled Prover-Verifier Games

    Feb 26, 2026Yegon Kim, Juho LeeLLM Reliability

    KAIST

  25. Probing for Knowledge Attribution in Large Language Models

    Feb 26, 2026Ivo Brink, Alexander Boer, Dennis UlmerLLM InterpretabilityHallucination in Language Models

    KPMG NL / University of Amsterdam Amsterdam, The Netherlands · KPMG NL Amsterdam, The Netherlands · University of Amsterdam Amsterdam, The Netherlands

  26. FinReasoning: A Hierarchical Benchmark for Reliable Financial Research Reporting

    Feb 25, 2026Yiyun Zhu, Yidong Jiang, Ziwen Xu +4Financial Reasoning in Language ModelsFinancial Reasoning Benchmarks

    School of Computer Science and Technology, Tongji University, Shanghai, China · Shanghai Artificial Intelligence Laboratory, Shanghai, China

  27. PaperTrail: A Claim-Evidence Interface for Grounding Provenance in LLM-based Scholarly Q&A

    Feb 24, 2026Anna Martin-Boyle, Cara A. C. Leckey, Martha C. Brown +1LLM Answer VerificationLLM Reliability

    University of Minnesota Minneapolis, Minnesota, USA · NASA Langley Research Center Hampton, Virginia, USA

  28. Three Concrete Challenges and Two Hopes for the Safety of Unsupervised Elicitation

    Feb 23, 2026Callum Canavan, Aditya Shrivastava, Allison Qi +2LLM ReliabilityLanguage Model Safety Evaluation

    MATS · Anthropic Fellows Program · Anthropic

  29. What Makes a Good Query? Measuring the Impact of Human-Confusing Linguistic Features on LLM Performance

    Feb 23, 2026William Watson, Nicole Cho, Sumitra Ganesh +1Hallucination in Language ModelsLLM Reliability

    J.P. Morgan AI Research

  30. LLM-enabled Applications Require System-Level Threat Monitoring

    Feb 23, 2026Yedi Zhang, Haoyu Wang, Xianglin Yang +2LLM SecurityLLM Reliability

    Department of Computer Science, National University of Singapore, Singapore · School of Computing and Information Systems, Singapore Management University, Singapore