Overview

Epistemic uncertainty concerns what a model does not know, often distinguished from aleatoric uncertainty caused by inherent variability or ambiguity in observations. Researchers estimate it with Bayesian methods, ensembles and dropout, evidential models, and set-valued or credal predictions, then use it for out-of-distribution detection, selective prediction, active learning, and safer decisions. Work increasingly evaluates whether uncertainty is calibrated and useful for specific decisions, including through conformal guarantees, abstention tests, and benchmarks under distribution shift. A central tension is that common signals such as ensemble disagreement or predictive entropy may not reliably track missing knowledge, and their value depends on how uncertainty is defined and tested.

Latest papers

CardsList

113 papers14 papers in the last four weeks, up 250% on the four weeks before. 0.1% of all new papers.

  1. Descriptive versus Regulatory Uncertainty in Bounded Predictive Systems

    May 17, 2026Ahmed Gamal EldinLLM Uncertainty EstimationEpistemic Uncertainty

  2. Random-Set Graph Neural Networks

    May 12, 2026Tommy Woodley, Shireen Kudukkil Manchingal, Matteo Tolloso +2Graph Neural NetworksUncertainty Quantification

  3. The Minimax Rate of Perturbed Second-Order Calibration

    May 8, 2026Kamil Ciosek, Banafsheh Rafiee, Sina Ghiassian +1Post-Hoc CalibrationMinimax Estimation

  4. GEM-FI: Gated Evidential Mixtures with Fisher Modulation

    May 5, 2026Marco Mustafa Mohammed, Fatemeh Daneshfar, Pietro LiòEvidential Deep LearningOOD Detection

  5. Possibilistic Predictive Uncertainty for Deep Learning

    May 1, 2026Yao Ni, Jeremie Houssineau, Yew-Soon Ong +1Uncertainty QuantificationEpistemic Uncertainty

  6. Task-Conditioned Uncertainty Costmaps for Legged Locomotion

    Apr 30, 2026Kartikeya Singh, Christo Aluckal, Romeo Orsolino +1Robot LocomotionEpistemic Uncertainty

  7. Uncertainty-Aware Pedestrian Attribute Recognition via Evidential Deep Learning

    Apr 29, 2026Zhuofan Lou, Shihang Zhang, Fangle Zhu +2Evidential Deep LearningEpistemic Uncertainty

  8. Credal Concept Bottleneck Models for Epistemic-Aleatoric Uncertainty Decomposition

    Apr 27, 2026Tanmoy Mukherjee, Thomas Bailleux, Pierre Marquis +1Uncertainty QuantificationConcept Bottleneck Models

  9. Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification

    Apr 18, 2026Kimia Hamidieh, Veronika Thost, Walter Gerych +2Selective PredictionConfidence Estimation in Language Models

  10. EviDep: Uncertainty-Aware Multimodal Depression Estimation via Disentangled Evidential Learning

    Apr 17, 2026Fangyuan Liu, Sirui Zhao, Yangsong Zhang +5Disentangled Representation LearningEvidential Deep Learning

  11. Retrieval Is Not Enough: Why Organizational AI Needs Epistemic Infrastructure

    Apr 13, 2026Federico Bottino, Carlo Ferrero, Nicholas Dosio +1Knowledge RepresentationEpistemic Uncertainty

  12. Epistemic Robust Offline Reinforcement Learning

    Apr 8, 2026Abhilash Reddy Chenreddy, Erick DelageUncertainty Estimation in RLOffline RL

  13. Uncertainty-Aware Foundation Models for Clinical Data

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

  14. Variational LSTM with Augmented Inputs: Nonlinear Response History Metamodeling with Aleatoric and Epistemic Uncertainty

    Apr 2, 2026Manisha Sapkota, Min Li, Bowei LiSurrogate ModelingUncertainty Propagation

  15. Uncertainty Gating for Cost-Aware Explainable Artificial Intelligence

    Mar 31, 2026Georgii Mikriukov, Grégoire Montavon, Marina M. -C. HöhneExplainable Artificial IntelligenceExplainability Evaluation

  16. An Isotropic Approach to Efficient Uncertainty Quantification with Gradient Norms

    Mar 31, 2026Nils Grünefeld, Jes Frellsen, Christian HardmeierUncertainty QuantificationLLM Uncertainty Estimation

  17. Quantification of Credal Uncertainty: A Distance-Based Approach

    Mar 28, 2026Xabier Gonzalez-Garcia, Siu Lun Chau, Julian Rodemann +6Uncertainty QuantificationAleatoric Uncertainty

  18. The Anatomy of Uncertainty in LLMs

    Mar 26, 2026Aditya Taparia, Ransalu Senanayake, Kowshik Thopalli +1LLM AuditingLLM Reliability

  19. Rethinking Uncertainty Quantification and Entanglement in Image Segmentation

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

  20. FoMo X: Modular Explainability Signals for Outlier Detection Foundation Models

    Mar 18, 2026Simon Klüttermann, Tim Katzke, Phuong Huong Nguyen +1Interpretable Anomaly DetectionUnsupervised Anomaly Detection

  21. The Geometry of Knowing: From Possibilistic Ignorance to Probabilistic Certainty -- A Measure-Theoretic Framework for Epistemic Convergence

    Mar 13, 2026Moriba Kemessia JahImprecise ProbabilityEpistemic Uncertainty

  22. CUPID: A Plug-in Framework for Joint Aleatoric and Epistemic Uncertainty Estimation with a Single Model

    Mar 11, 2026Xinran Xu, Xiuyi FanUncertainty QuantificationEpistemic Uncertainty

  23. Verbalizing LLM's Higher-order Uncertainty via Imprecise Probabilities

    Mar 11, 2026Anita Yang, Krikamol Muandet, Michele Caprio +2Imprecise ProbabilityLLM Uncertainty Estimation

  24. From Scalars to Tensors: Declared Losses Recover Epistemic Distinctions That Neutrosophic Scalars Cannot Express

    Mar 10, 2026Tony MasonEpistemic UncertaintyLLM Evaluation