Reliable Uncertainty Quantification

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Period ending 2026-09-21

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Period ending 2026-09-07

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  1. Accelerating Evolutionary Strategy via Rao-Blackwellizing Realization of Uncertain Input

    Aug 3, 2026So Nakashima, Tetsuya J. KobayashiEvolutionary SearchRobust Optimization

  2. Deep Evidential Regression for Sparse Forest Height Estimation from Multimodal Satellite Imagery

    Aug 3, 2026Laura Bader, Muhammad Ammar Ahmed, Xiao Xiang Zhu +1CanopySatellite Data

  3. Imprecise Belief Fusion Improves Multi-agent Social Learning

    Aug 2, 2026Zixuan Liu, Jonathan Lawry, Michael CrosscombeUncertainty-Aware FusionSingular Learning Theory

  4. An Uncertainty-Driven Hybrid Deep Learning Approach for Broad-Coverage RF Modulation Recognition

    Aug 1, 2026Nurettin Safak, Durdu Can Yerdeyatar, Muhammet Sefa Demirel +3Automatic Modulation ClassificationRadio Frequency

  5. TrAC: Trace-Conditioned Answer Consistency for Efficient Uncertainty Quantification in LLMs

    Aug 1, 2026Dahai Yu, Lin Jiang, Rongchao Xu +1Large Language Model UncertaintyLarge Language Model Reasoning

  6. SymboUQ: Symbolic Uncertainty Quantification for Spatial Reasoning in LLMs

    Aug 1, 2026Dahai Yu, Lin Jiang, Rongchao Xu +1Spatial ReasoningReasoning Traces

  7. Sycophancy Undermines Epistemic Vigilance in Cooperative Vision-Language Tasks

    Jul 31, 2026Rupak Sarkar, Neha Srikanth, Saloni Gupta +3Epistemic StanceSycophancy

  8. GO-PRE: Goal-Oriented Next-Best-View Selection via Predictive Rendering Entropy for Active 3D Reconstruction

    Jul 31, 2026Yan Song, Zhihao Li, Chenglong Li +33D Reconstruction3D Object Understanding

  9. Structured Neural Chaos: An Adaptive Surrogate Modeling Framework for Functional Uncertainty Quantification and Global Sensitivity Analysis

    Jul 31, 2026Isabel Corona Guevara, Yeping HuSurrogate ModelsModel Sensitivity

  10. Uncertainty quantification for trustworthy deep learning: Methods and measures

    Jul 30, 2026H. Martin Gillis, Thomas TrappenbergReliable Uncertainty QuantificationBayesian Neural Networks

  11. The Geometry of Flow-Matching Uncertainty: A Cost-free Uncertainty Proxy and Its Application in Flow-based VLA Failure Detection

    Jul 30, 2026Ziyang Rao, Yiren Zhao, Weiyu Guo +3Velocity FieldInput Uncertainties

  12. Cost-Sensitive Conformal Prediction and Human-in-the-Loop Abstention for Imbalanced High-Stakes Decision Support: A Multi-Domain Benchmark

    Jul 29, 2026Manpreet Singh, Akshatha Srikantha, Shyamal LakhanpalFinite-Sample Coverage GuaranteesDecision Thresholds

  13. From Keypoints to Predictive Distributions: Post-Hoc Uncertainty for YOLO-Pose Models

    Jul 29, 2026Alexej Klushyn, Juan Rivero Sesma, Florian Seligmann +3Calibrated UncertaintyKeypoint Detection

  14. Collaborative Weighting with Pessimistic Critic for Mitigating Overestimation in Off-Policy Reinforcement Learning

    Jul 29, 2026Gong Gao, Xiao Lai, Ziqi Xie +3Off-Policy EvaluationOverconfidence

  15. HeAD-CP: Heterophily-Aware Diffused Conformal Prediction Sets for Graph Neural Networks

    Jul 28, 2026Phan Binh Nguyen Lam, Nguyen Thai AnhGraph Neural NetworksConformal Prediction

  16. Beyond "What to Retrieve": Uncertainty in Retrieval-Augmented Code Generation

    Jul 27, 2026Chandan Kumar Sah, Li Zhang, Xiaoli LianCode GenerationInput Uncertainties

  17. Covariance Last-Layer Ensembles: Function-Space Diversity for Efficient Uncertainty Quantification

    Jul 26, 2026H. Martin Gillis, Isaac Xu, Gabriel Spadon +1EnsembleCovariance Estimation

  18. From Hybrid Mechanistic--Data-Driven Modeling Toward Neuro-Symbolic AI: What, Why, and How

    Jul 24, 2026Moein E. Samadi, Andreas SchuppertNeuro-Symbolic FrameworkHybrid

  19. Smart predict-then-robustly-optimize

    Jul 23, 2026Aakil Caunhye, Xuefei Lu, Belen Martin-BarraganRobust OptimizationPredictive Uncertainty

  20. Interval and fuzzy physics-augmented neural networks (iPANN and fPANN) for uncertainty quantification and propagation in constitutive modeling

    Jul 22, 2026Somesh Pratap Singh, Govinda Anantha Padmanabha, Jingye Tan +4Conventional Physics-Informed Neural NetworksReliable Uncertainty Quantification

  21. Bayesian uncertainty estimation improves clinical decision making in medical AI agents

    Jul 22, 2026Frederik Hauke, Patrick Wienholt, Christiane Kuhl +4Epistemic UncertaintyClinical Decision Support

  22. Post-Training in Time Series Foundation Models: A Unifying Framework

    Jul 22, 2026Shifeng Xie, Ambroise Odonnat, Zehao Xiao +7Time Series Foundation ModelsLLM Post-Training Methods

  23. Good Practice Guide for quantifying uncertainties for machine learning models applied to photoplethysmography signals

    Jul 22, 2026P. Harris, C. Bench, M. Rinkevičius +6Remote PhotoplethysmographyReliable Uncertainty Quantification

  24. Probabilistic Physics-Aware Machine Learning Predictions of Electric Truck Energy Consumption with Field Data

    Jul 21, 2026Hannes Nilsson, Rafael Basso, Balázs Kulcsár +1Electricity Price ForecastingElectric Vehicles

  25. It's Not What You Say, It's How You Say It: Evaluating LLM Responses to Expressions of Belief

    Jul 20, 2026Kevin Du, Clara Kümpel, Michelle Wastl +1Large Language Model ResponsesLinguistics

  26. Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting

    Jul 20, 2026Ziteng Li, Yanan Xin, Tina Comes +1Zero-Shot ForecastingPedestrian Trajectory Prediction

  27. Honest Physical-Support Inference after Latent Dictionary Learning: Collision Singularities and Minimax Resolution

    Jul 18, 2026Guan-Ju PengSparse RecoverySingle-Photon Avalanche Diode

  28. Isotonic Conformal Prediction

    Jul 18, 2026Daniel Bensimon, Sean Xiang Yu, Eric D. Kolaczyk +1Conformal PredictionReliable Uncertainty Quantification

  29. Certifiable Safe Model-Based Reinforcement Learning with Control-Affine Dynamics Approximation

    Jul 17, 2026Hao Zhou, Yanze Zhang, Cameron Reid +1Control Barrier FunctionsScalable Robot Learning

  30. Evaluating Epistemic Uncertainty: Beyond OOD Detection and Active Learning

    Jul 16, 2026Jakub Paplhám, Willem Waegeman, Eyke Hüllermeier +1Epistemic UncertaintyBayesian

  31. Full-data accuracy with fewer labels for training and fine-tuning machine-learning force fields

    Jul 16, 2026Sheng Bi, Yi-Ze Wang, Jun ChengActive LearningLabel-Free

  32. Decision Making Needs Uncertainty Quantification [Lecture Notes]

    Jul 15, 2026Osvaldo SimeoneEpistemic UncertaintyDecisions

  33. Posterior Variance Is a Constraint Map, Not an Error Map: Closed-Form Uncertainty for Radiative Gaussian Splatting in Sparse-View CT

    Jul 15, 2026Chulin Zhao, Yiran Xu, Shu LiuCalibrated UncertaintyGaussian Splatting

  34. Robustness of Deep Learning Models for PV Power Forecasting under NWP Forecast Errors: A Spatiotemporal and Physically Interpretable Analysis

    Jul 14, 2026Dandan Chen, Yan Zhao, Xuepeng ChenEnergy ForecastingNumerical Weather Prediction

  35. Epistemic Stance Flexibility Probing: Measuring Prompt-Conditioned Register Shift in Large Language Models

    Jul 14, 2026Binwen Liu, Yilin RenEpistemic StanceTweet-Level Stance Detection

  36. Code-MUE: Measuring Code LLMs' Uncertainty through Execution-based Semantic Interaction Graphs

    Jul 14, 2026Xiaoning Ren, Yinxing Xue, Lei Ma +1Large Language Model UncertaintyInput Uncertainties

  37. Dynamic Online Processor-Native Inference for State Estimation

    Jul 13, 2026Orestis KaparounakisParticle FiltersState Estimation

  38. Climate-Invariant Conformal Prediction Intervals for Multi-Horizon Solar and Wind Forecasting

    Jul 13, 2026Shreedhar Gangwar, Abhinav Bains, Banalaxmi BrahmaEnergy ForecastingSolar

  39. Uncertainty Quantification for EO Regression Tasks: Building Height, Tree Canopy Height and Above-ground Biomass Estimation

    Jul 13, 2026Ritu Yadav, Andrea Nascetti, Yifang BanCanopyAbove-Ground Biomass

  40. Adapting Evidential Neural Networks to Test-Time Neighbor Fusion Improves Molecular Property Prediction

    Jul 13, 2026Cameron Gruich, Weichi Yao, Yixin Wang +1Molecular Property PredictionEvidential Learning

  41. TSCoNet: A Two-Stage Copula CNN-LSTM for Uncertainty-Aware Spatio-Temporal Forecasting

    Jul 11, 2026Jongwook Kim, Jong-Min KimSpatio-Temporal ForecastingPredictive Uncertainty

  42. Learning Predictive Ambiguity Sets for Decision-Focused Distributionally Robust Optimization

    Jul 10, 2026Junjie GuoRobust OptimizationPredictive Uncertainty

  43. Robust Bayesian Decision Making under Adversarial Uncertainty

    Jul 9, 2026Haripriya Harikumar, Sammie Katt, Yasir Zubayr Barlas +1Bayesian Experimental DesignBayesian

  44. When Thinking Hurts: Epistemic Signals in the Reasoning Chains of Visual Language Models

    Jul 9, 2026Mayank SingalQwen3-Embedding-8BVisual Reasoning

  45. Validating LLMs in social science: Epistemic threats and emerging norms

    Jul 8, 2026Meera Desai, Dallas Card, Abigail Z. JacobsComputational Social ScienceLarge Language Model Reliability

  46. Hypergraph Neural Stochastic Diffusion: An SDE Framework for Uncertainty Estimation

    Jul 8, 2026Zhiheng Zhou, Mengyao Zhou, Dengyi Zhao +2HypergraphsPredictive Uncertainty

  47. Efficient Bayesian Deep Ensembles via Analytic Predictive Inference

    Jul 7, 2026Sina Aghaee Dabaghan Fard, Marie Maros, Jaesung LeeBayesian Neural NetworksEnsemble

  48. Hypothesis-driven Model Expansion under Uncertainty for Open-World Robot Planning

    Jul 7, 2026Anxing Xiao, Hanbo Zhang, Tianrun Hu +1Robot PlanningClassical Planning

  49. UASPL: Uncertainty-Aware Self-Paced Learning with Evidential Neural Networks

    Jul 7, 2026Yifan Zhang, Yuxin Hu, Zhuobin Hao +2Uncertainty-Aware InferenceLoss Function

  50. Estimating Uncertainty from Reasoning: A Large-Scale Study of Multi- and Crosslingual MCQA Performance in LLMs

    Jul 7, 2026Andrea Bacciu, Andrea Alfarano, Saab Mansour +2Large Language Model UncertaintyReducible Uncertainty

  51. Heckman-Corrected Epistemic Uncertainty: Selection on Unobservables Defeats Importance Weighting

    Jul 7, 2026Gunner Levi HoweSelection BiasCovariate Shift

  52. SpanUQ: Span-Level Uncertainty Quantification for Large Language Model Generation

    Jul 7, 2026Yimeng Zhang, Yingying Zhuang, Ziyi Wang +12Large Language Model UncertaintyInput Uncertainties

  53. Rendering-Aware Bayesian 3D Gaussian Splatting with Native Uncertainty and Adaptive Complexity Control

    Jul 6, 2026Gaoxiang Jia, Vikram Appia, Junzhou Huang +13D Gaussian Splats3D Gaussian

  54. Uncertainty-aware damage identification in short-span bridges via physics-informed variational autoencoder

    Jul 6, 2026Ana Fernandez-Navamuel, A. Javier Omella, Diego Zamora-Sanchez +1Structural Health MonitoringVariational Autoencoder

  55. Adaptive Diversity-Uncertainty Active Learning with Redundancy Control for Bioacoustic Event Classification

    Jul 6, 2026Gabriel Dubus, Hugo Magaldi, Anatole Gros-MartialPassive Acoustic MonitoringActive Learning

  56. Joint distribution of upstream runoff governs downstream river-discharge prediction uncertainty in distributed ML models

    Jul 3, 2026Karan Ruparell, Tristan Hascoet, Takemasa Miyoshi +4Fundamental Hydrological PrinciplesAccurate Flood Prediction

  57. AI Virtue: What is "Good" Knowledge in the Age of Artificial Intelligence?

    Jul 2, 2026Alan LiuArtificial Intelligence LiteracyArtificial Intelligence Systems

  58. Certified World Models as Sensing Clocks: Drift-Aware Deadlines for Active Perception

    Jul 1, 2026Hongbo WangClocksDeadlines

  59. From Prediction Uncertainty to Conformalized Distance Fields for Safe Motion Planning

    Jul 1, 2026Jaeuk Shin, Yoonseok Ra, Insoon YangMotion PlannersConformal Prediction

  60. Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines

    Jul 1, 2026Eliott Thomas, Mickael Coustaty, Aurelie Joseph +3Active LearningObject Detection