Uncertainty Calibration

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Overview

Uncertainty calibration studies whether predictions reported as confident or uncertain match how often they are correct, and whether predictive intervals achieve their stated coverage. Common approaches include post-hoc temperature or isotonic scaling, conformal prediction, and uncertainty-aware training with Bayesian models, ensembles, or evidential methods; language-model work also calibrates semantic or verbal confidence for abstention and routing. Methods are tested across classification, forecasting, medical imaging, robotics, and language tasks, often under distribution shift. A central challenge is that good average calibration may hide unreliable subgroups or extreme cases, while improving calibration can trade off against sharpness, accuracy, error ranking, or the limited supply of representative validation data.

Latest papers

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265 papers31 papers in the last four weeks, up 63% on the four weeks before. 0.2% of all new papers.

  1. Budget-Aware Uncertainty for Radiotherapy Segmentation QA Using nnU-Net

    Apr 13, 2026Ricardo Coimbra Brioso, Lorenzo Mondo, Damiano Dei +4Segmentation Uncertainty EstimationMedical Image Segmentation

    Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy · Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy · Radiotherapy and Radiosurgery Department, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy

  2. MedFormer-UR: Uncertainty-Routed Transformer for Medical Image Classification

    Apr 10, 2026Mohammed Maaz Sibhai, Abedalrhman Alkhateeb, Saad B. AhmedMedical Image ClassificationVision Transformer

    [1] Department of Computer Science, Lakehead University

  3. Accurate and Reliable Uncertainty Estimates for Deterministic Predictions Extensions to Under and Overpredictions

    Apr 9, 2026Rileigh Bandy, Enrico Camporeale, Andong Hu +2Distributional RegressionUncertainty Quantification

    Optimization and Uncertainty Quantification Department, Sandia National Laboratories, Albuquerque, NM · School of Physical and Chemical Sciences, Queen Mary University of London, London, UK and Space Weather Technology, Research and Education Center, University of Colorado, Boulder, CO · Space Weather Technology, Research and Education Center, University of Colorado, Boulder, CO +2

  4. VOLTA: The Surprising Ineffectiveness of Auxiliary Losses for Calibrated Deep Learning

    Apr 9, 2026Rahul D Ray, Utkarsh SrivastavaUncertainty QuantificationUncertainty Calibration

    Department of Electronics & Electrical Engineering BITS Pilani, Hyderabad Campus. · Department of Economics & Finance BITS Pilani, Hyderabad Campus

  5. Canopy Tree Height Estimation Using Quantile Regression: Modeling and Evaluating Uncertainty in Remote Sensing

    Apr 8, 2026Karsten Schrödter, Jan Pauls, Fabian GiesekeRemote SensingUncertainty Calibration

    University of Münster · University of Copenhagen

  6. Uncertainty Estimation for Deep Reconstruction in Actuatic Disaster Scenarios with Autonomous Vehicles

    Apr 7, 2026Samuel Yanes Luis, Alejandro Casado Pérez, Alejandro Mendoza Barrionuevo +3Uncertainty QuantificationUncertainty Calibration

    Department of Electronic Technology, University of Sevilla, Av. de la Reina Mercedes S/N, 41012, Sevilla, Spain. · Department of Electronic Engineering, University of Sevilla, Av. de los Descubrimientos S/N, 41005, Sevilla, Spain.

  7. Uncertainty-Aware Foundation Models for Clinical Data

    Apr 5, 2026Qian Zhou, Yuanyun Zhang, Shi LiEpistemic UncertaintyMultimodal Foundation Models

    University of the Chinese Academy of Sciences · Columbia University

  8. Neural Processes Maintain Calibrated Biomass Estimates Across Spatiotemporal Gaps and Disturbance

    Apr 4, 2026Robin Young, Srinivasan KeshavForest Aboveground Biomass EstimationNeural Processes

    Department of Computer Science and Technology, University of Cambridge, Cambridge, CB3 0FD, Cambridgeshire, UK

  9. Towards Intrinsically Calibrated Uncertainty Quantification in Industrial Data-Driven Models via Diffusion Sampler

    Apr 2, 2026Yiran Ma, Jerome Le Ny, Zhichao Chen +1Uncertainty QuantificationUncertainty Calibration

    College of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China · Electrical Engineering Department, Polytechnique Montreal, and with GERAD, Montreal, QC H3T 1J4, Canada · State Key Lab of General AI, School of Intelligence Science and Technology, Peking University, Beijing 100871, China +1

  10. UQ-SHRED: uncertainty quantification of shallow recurrent decoder networks for sparse sensing via engression

    Apr 1, 2026Mars Liyao Gao, Yuxuan Bao, Amy S. Rude +2Distributional RegressionUncertainty Quantification

    Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, USA · Department of Applied Mathematics, University of Washington, Seattle, WA, USA · Department of Statistics, University of Washington, Seattle, WA, USA +1

  11. Towards Reliable Truth-Aligned Uncertainty Estimation in Large Language Models

    Apr 1, 2026Ponhvoan Srey, Quang Minh Nguyen, Xiaobao Wu +1LLM Uncertainty EstimationUncertainty Calibration

    Nanyang Technological University, Singapore · KAIST, South Korea · Shanghai Jiao Tong University

  12. Measuring (some aspects of) the metacognition of AI

    Mar 31, 2026Richard Servajean, Philippe ServajeanLLM EvaluationLLM Uncertainty Estimation

    Center for Brain Science, RIKEN, Saitama, Japan. · National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan. · Department of Psychology, Paul-Val´ery University, Montpellier, France.

  13. Energy Score-Guided Neural Gaussian Mixture Model for Predictive Uncertainty Quantification

    Mar 29, 2026Yang Yang, Chunlin Ji, Haoyang Li +1Uncertainty QuantificationUncertainty Calibration

    School of Statistics and Data Science, Nankai University, Tianjin, China · Kuang-Chi Institute of Advanced Technology, Shenzhen, China · Department of Computing, The Hong Kong Polytechnic University, Hong Kong SAR, China +1

  14. Multi-Agent Reasoning with Consistency Verification Improves Uncertainty Calibration in Medical MCQA

    Mar 25, 2026John Ray B. MartinezUncertainty CalibrationMedical QA

    Department of Data Science and Analytics, Harrisburg University of Science and Technology

  15. Beyond Static Uncertainty: Modeling Temporal Uncertainty Dynamics for Probabilistic Time Series Forecasting

    Mar 25, 2026Yijun Wang, Qiyuan Zhuang, Larysa Marchanka +1Probabilistic Time Series ForecastingUncertainty Quantification

    Department of Computer Science, Southeast University, Nanjing, China · Francisk Skorina Gomel State University, Belarus

  16. Rethinking Uncertainty Quantification and Entanglement in Image Segmentation

    Mar 19, 2026Jakob Lønborg Christensen, Vedrana Andersen Dahl, Morten Rieger Hannemose +2Uncertainty QuantificationDeep Ensembles

    Technical University of Denmark, DTU Compute · University of Lucerne, Faculty of Health Sciences and Medicine, Switzerland

  17. Shifting Uncertainty to Critical Moments: Towards Reliable Uncertainty Quantification for VLA Model

    Mar 18, 2026Yanchuan Tang, Taowen Wang, Yuefei Chen +3Uncertainty Estimation for VLA ModelsUncertainty Calibration

    Rutgers University · Kent State University

  18. Predictive Uncertainty in Short-Term PV Forecasting under Missing Data: A Multiple Imputation Approach

    Mar 16, 2026Parastoo Pashmchi, Jérôme Benoit, Motonobu KanagawaSolar Power ForecastingUncertainty Propagation

    SAP Labs France, Mougins, France · EURECOM, Biot, France

  19. Self-Supervised Uncertainty Estimation For Super-Resolution of Satellite Images

    Mar 14, 2026Zhe Zheng, Valéry Dewil, Pablo AriasImage Super-ResolutionRemote Sensing Image Super-Resolution

    Centre Borelli, ENS Paris-Saclay, Universite Paris-Saclay, CNRS, Gif-sur-Yvette, France · Dept. of Engineering, Universitat Pompeu Fabra, Barcelona, SPAIN

  20. I Know What I Don't Know: Latent Posterior Factor Models for Multi-Evidence Probabilistic Reasoning

    Mar 13, 2026Aliyu Agboola AlegeLatent Variable ModelsUncertainty Calibration

    Epalea

  21. Trustworthy Predictive Distributions for Tail Events with Semiparametric Diagnostic Transport Maps

    Mar 11, 2026Elizabeth Cucuzzella, Rafael Izbicki, Ann B. LeeProbability CalibrationProbabilistic Forecasting

    Department of Statistics and Data Science, Carnegie Mellon University · Department of Statistics, Federal University of Sao Carlos

  22. Beyond Accuracy: Reliability and Uncertainty Estimation in Convolutional Neural Networks

    Mar 11, 2026Sanne Ruijs, Alina Kosiakova, Farrukh JavedUncertainty QuantificationUncertainty Calibration

    Department of Economics, Lund University, Sweden · Department of Statistics, Lund University, Sweden

  23. Rethinking Gaussian Trajectory Predictors: Calibrated Uncertainty for Safe Planning

    Mar 11, 2026Fatemeh Cheraghi Pouria, Mahsa Golchoubian, Katherine Driggs-CampbellPedestrian Trajectory PredictionSafe Motion Planning

    Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Champaign, IL 61820 USA · Department of Mathematical and Computational Sciences, University of Toronto, Toronto, Canada

  24. Variational Routing: A Scalable Bayesian Framework for Calibrated Mixture-of-Experts Transformers

    Mar 10, 2026Albus Yizhuo Li, Matthew WickerUncertainty QuantificationMixture-of-Experts Models

    Department of Computing, Imperial College London.

  25. Bayesian Transformer for Probabilistic Load Forecasting in Smart Grids

    Mar 9, 2026Sajib Debnath, Md. Uzzal MiaElectricity Load ForecastingProbabilistic Time Series Forecasting

    O&M Analytics, AES Clean Energ; The AES Corporation; Louisville, CO 80027, USA · Department of Information and Communication Engineering; Pabna University of Science and Technology; Rajapur, Pabna, Bangladesh

  26. Uncertainty-Gated Generative Modeling

    Mar 8, 2026Xingrui Gu, Haixi ZhangTime Series ForecastingGenerative Modeling

    Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, USA · School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA

  27. To Predict or Not to Predict? Towards reliable uncertainty estimation in the presence of noise

    Mar 7, 2026Nouran Khallaf, Serge SharoffMultilingual Text ClassificationUncertainty Calibration

    Centre for Translation, Localisation and Interpreting Studies, School of Languages, Cultures and Societies, University of Leeds, UK

  28. Confidence Before Answering: A Paradigm Shift for Efficient LLM Uncertainty Estimation

    Mar 6, 2026Changcheng Li, Jiancan Wu, Hengheng Zhang +5Confidence Estimation in Language ModelsLLM Uncertainty Estimation

    University of Science and Technology of China · Huawei Inc.

  29. Uncertainty quantification in neural network-based glucose prediction for diabetes

    Mar 5, 2026Hai Siong Tan, Rafe McBethBlood Glucose ForecastingUncertainty Calibration

    Gryphon Center for A.I. and Theoretical Sciences, Singapore · University of Pennsylvania, Perelman School of Medicine, Philadelphia, USA

  30. ELLIPSE: Evidential Learning for Robust Waypoints and Uncertainties

    Mar 4, 2026Zihao Dong, Chanyoung Chung, Dong-Ki Kim +5Robot Imitation LearningTrajectory Prediction

    FieldAI. · Northeastern University, Boston, MA, USA.