LLM Uncertainty Estimation

LLM: Large Language Model

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38 papers in the last four weeks, up 111% on the four weeks before. 0.4% of all new papers.

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Why Semantic Entropy Fails: Geometry-Aware and Calibrated Uncertainty for Policy Optimization
May 20, 2026Zheyuan Zhang, Kaiwen Shi, Han Bao +3RL for Language Model Reasoning Policy Optimization
University of Notre Dame · †Corresponding Author
Probabilistic Attribution For Large Language Models
May 20, 2026Shilpika Shilpika, Carlo Graziani, Bethany Lusch +2LLM Interpretability LLM Uncertainty Estimation
Argonne Leadership Computing Facility Argonne National Laboratory Lemont, IL, USA · Mathematics and Computer Science Division Argonne National Laboratory Lemont, IL, USA · Department of Computer Science University of Illinois Chicago Chicago, IL, USA
Reading Calibrated Uncertainty from Language Model Trajectories
May 19, 2026Aliai Eusebi, Alexander Herzog, Xiaoyu Liang +3Confidence Estimation in Language Models LLM Reliability
University College London, London, United Kingdom · Core46, London, United Kingdom
Retrieval-Augmented Linguistic Calibration
May 19, 2026Yi-Fan Yeh, Linwei Tao, Minjing Dong +4Confidence Estimation in Language Models Language Model Calibration
School of Computer Science University of Sydney Sydney, Australia · City University of Hong Kong Hong Kong · Shanghai Jiao Tong University Shanghai, China +1
Diagnosing Multi-step Reasoning Failures in Black-box LLMs via Stepwise Confidence Attribution
May 19, 2026Xiaoou Liu, Tiejin Chen, Dengjia Zhang +3Uncertainty Quantification Confidence Estimation in Language Models
1Arizona State University · 2Johns Hopkins University · 3Purdue +1
Position: Uncertainty Quantification in LLMs is Just Unsupervised Clustering
May 19, 2026Tiejin Chen, Longchao Da, Xiaoou Liu +1LLM Evaluation Uncertainty Quantification
School of Computing and Augmented Intelligence, Arizona State University
Descriptive versus Regulatory Uncertainty in Bounded Predictive Systems
May 17, 2026Ahmed Gamal EldinLLM Uncertainty Estimation Epistemic Uncertainty
Nova University Lisbon – Cairo Branch (NOVA IMS), Cairo, Egypt
BELIEF: Structured Evidence Modeling and Uncertainty-Aware Fusion for Biomedical Question Answering
May 17, 2026Chang Zong, Hao Ning, Siliang Tang +2Healthcare Evidence-Grounded Reasoning
Confidence Geometry Reveals Trace-Level Correctness in Large Language Model Reasoning
May 16, 2026Shuo Liu, Ding Liu, Shi-Ju RanConfidence Estimation in Language Models LLM Reliability
School of Computer Science and Technology, Tiangong University, Tianjin, China. · Center for Quantum Physics and Intelligent Sciences, Department of Physics, Capital Normal University, Beijing, China.
Distributional Energy-Based Models for Uncertainty-Aware Structured LLM Reasoning
May 15, 2026Shireen Kudukkil Manchingal, Abhey Kalia, Fernanda Gonçalves +1LLM Answer Verification Energy-Based Models
Oxford Dynamics · Harwell Science and Innovation Campus, United Kingdom
Calibrating LLMs with Semantic-level Reward
May 15, 2026Fengfei Yu, Ruijia Niu, Dongxia Wu +2Language Model Calibration LLM Reliability
Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA · Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, California, USA · Department of Statistics, Stanford University, Stanford, California, USA
Margin-Adaptive Confidence Ranking for Reliable LLM Judgement
May 14, 2026Gaojie Jin, Yong Tao, Lijia Yu +1LLM Evaluation LLM-as-a-Judge
Department of Computer Science, University of Exeter · Institute of AI for Industries, Chinese Academy of Sciences · Department of Mathematics and Computer Science, Eindhoven University of Technology
Uncertainty Quantification for Large Language Diffusion Models
May 14, 2026Artem Vazhentsev, Vladislav Smirnov, David Li +3Uncertainty Quantification LLM Hallucination Detection
1MBZUAI · 2The University of Melbourne
When Evidence Conflicts: Uncertainty and Order Effects in Retrieval-Augmented Biomedical Question Answering
May 13, 2026Yikun Han, Mengfei Lan, Halil KilicogluSelective Prediction Healthcare
University of Illinois Urbana-Champaign
Inducing Artificial Uncertainty in Language Models
May 13, 2026Sophia Hager, Simon Zeng, Nicholas AndrewsConfidence Estimation in Language Models Language Model Calibration
Johns Hopkins University · Microsoft
LLMs as Implicit Imputers: Uncertainty Should Scale with Missing Information
May 13, 2026Stef van BuurenLLM Evaluation Confidence Estimation in Language Models
1. TNO - Netherlands Organization for Applied Scientific Research, Leiden · 2. Dept. of Methodology and Statistics, University of Utrecht
ORCE: Order-Aware Alignment of Verbalized Confidence in Large Language Models
May 12, 2026Chen Li, Xiaoling Hu, Songzhu Zheng +2Confidence Estimation in Language Models Language Model Calibration
Stony Brook University, NY, USA · Massachusetts General Hospital and Harvard Medical School, MA, USA · Morgan Stanley, NY, USA
Uncertainty Quantification for LLM-based Code Generation
May 12, 2026Senrong Xu, Yuhao Tan, Yanke Zhou +6Uncertainty Quantification LLM Uncertainty Estimation
State Key Lab of Novel Software Technology, Nanjing University · ETH Zürich · Birkbeck, University of London
Assessing and Mitigating Miscalibration in LLM-Based Social Science Measurement
May 12, 2026Jinyuan Wang, Ningyuan Deng, Yi YangLanguage Model Calibration LLM Reliability
The Hong Kong University of Science and Technology
Agent-BRACE: Decoupling Beliefs from Actions in Long-Horizon Tasks via Verbalized State Uncertainty
May 12, 2026Joykirat Singh, Zaid Khan, Archiki Prasad +5Partially Observable RL Bayesian Inference
UNC Chapel Hill · Microsoft Research · The University of Texas at Austin
AcuityBench: Evaluating Clinical Acuity Identification and Uncertainty Alignment
May 12, 2026Robin Linzmayer, Georgianna Lin, Di Coneybeare +22Healthcare Clinical Triage
Department of Computer Science, Columbia University · Department of Biomedical Informatics, Columbia University · Department of Computer Science, Columbia University, New York, NY, USA +3
VERDI: Single-Call Confidence Estimation for Verification-Based LLM Judges via Decomposed Inference
May 11, 2026Jasmine Qi, Danylo Dantsev, Muyang SunPost-Hoc Calibration LLM-as-a-Judge
Indeed Inc.
Epistemic Uncertainty for Test-Time Discovery
May 11, 2026Kainat Riaz, Muhammad Ahmed Mohsin, Ahsan Bilal +5RL for Language Models RL Exploration
Stanford University · University of Oklahoma · National University of Sciences and Technology
Aligning LLM Uncertainty with Human Disagreement in Subjectivity Analysis
May 11, 2026Junyu Lu, Deyi Ji, Xuanyi Liu +5Annotator Disagreement LLM Alignment
School of Computer Science and Technology, Dalian University of Technology, China · Tencent · Peking University +1
ANCHOR: Abductive Network Construction with Hierarchical Orchestration for Reliable Probability Inference in Large Language Models
May 11, 2026Wentao Qiu, Guanran Luo, Zhongquan Jian +3Abductive Reasoning Bayesian Networks
School of Informatics, Xiamen University, Xiamen, China · School of Computer and Data Science, Minjiang University, Fuzhou, China · School of Film, Xiamen University, Xiamen, China +2
UCCI: Calibrated Uncertainty for Cost-Optimal LLM Cascade Routing
May 11, 2026Varun KotteCost-Aware Inference Language Model Calibration
Independent Researcher.
Trust or Abstain? A Self-Aware RAG Approach
May 11, 2026Xi Zhu, Ziqi Wang, Kai Mei +5Retrieval-Augmented Generation Knowledge Conflicts in Language Models
Rutgers University · University of Illinois Urbana-Champaign
The Metacognitive Probe: Five Behavioural Calibration Diagnostics for LLMs
May 11, 2026Rafael C. T. OliveiraLanguage Model Calibration LLM Uncertainty Estimation
Independent Researcher
A Semantic-Sampling Framework for Evaluating Calibration in Open-Ended Question Answering
May 8, 2026Zhanliang Wang, Jiancong Xiao, Ruochen Jin +3LLM Evaluation Confidence Estimation in Language Models
University of Pennsylvania, Philadelphia, PA · Dartmouth College, Hanover, NH
Uncertainty-Aware Structured Data Extraction from Full CMR Reports via Distilled LLMs
May 8, 2026Yi Yu, Parker Martin, Zhenyu Bu +5Clinical Information Extraction LLM Information Extraction
†The Ohio State University · ‡NetMind.AI

May 20, 2026, cs.LGJ/K move · Enter open · S save

Why Semantic Entropy Fails: Geometry-Aware and Calibrated Uncertainty for Policy Optimization

Zheyuan Zhang, Kaiwen Shi, Han Bao, Zehong Wang+2

University of Notre Dame · †Corresponding Author

RL for Language Model Reasoning Policy Optimization Language Model Calibration Policy Gradient Methods LLM Uncertainty Estimation RL Post-Training

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Post-training has become central to improving reasoning and alignment in large language models, where critic-free models enable scalable learning from model-generated outputs but lack principled mechanisms to distinguish informative from noisy signals. Recent approaches leverage response-level measures as uncertainty signals to regulate group-based optimization methods such as GRPO. Yet their empirical success remains unstable and unclear in how they influence optimization dynamics. In this paper, we provide, to our knowledge, the first principled formulation that interprets uncertainty signals as mechanisms for characterizing and regulating gradient variance and learning signal quality. Based on both empirical and theoretical analysis, we identify two critical gaps of current entropy-based estimators: The anisotropic gap and The calibration gap. Motivated by this analysis, we propose Geometric-aware Calibrated Policy Optimization (GCPO), a novel framework integrating geometry-aware measures to capture semantic disagreement with reward-based calibration to align uncertainty with learning signal strength. Experiments on multiple benchmarks show that our approach more faithfully tracks gradient variability and consistently improves post-training performance. Our results highlight the importance of designing uncertainty signals that are aligned with optimization dynamics, offering a principled perspective for robust post-training.

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