Uncertainty Quantification

Conformal Risk Sharing: Certified Cost Allocation with Participation Guarantees UAI 2026 Contrastive Conformal Sets UAI 2026 Controlling Uncertainty and Hallucination Risk in Multi-Agent Fact Verification UAI 2026 Credal Concept Bottleneck Models for Epistemic–Aleatoric Uncertainty Decomposition ACL 2026 CURA: Clinical Uncertainty Risk Alignment for Language Model–Based Risk Prediction ACL 2026 Debiased Machine Learning for Conformal Prediction of Counterfactual Outcomes Under Runtime Confounding CLeaR 2026 Decomposing Ensemble Spread in Lorenz ’96 with Learned Stochastic Parameterizations UAI 2026 Delving Aleatoric Uncertainty in Medical Image Segmentation via Vision Foundation Models CVPR 2026 Demystifying Uncertainty in LLMs: Active Calibration between Concepts and Human Evaluations ACL 2026 Detecting Hallucinations in Large Language Models via Internal Attention Divergence Signals ACL 2026 Diagnosing Hidden Instabilities in Model Editing via Uncertainty Quantification ACL 2026 DisCal: Distribution-Aware Calibration for Mathematical Reasoning Under Character-Level Noisy Inputs ACL 2026 Dissecting Failure Dynamics in Large Language Model Reasoning ACL 2026 DRL-ORA: Distributional Reinforcement Learning with Online Epistemic Risk Adaptation UAI 2026 DROID-SLAM in the Wild CVPR 2026 DUD: Decoupled Update Dynamics for Reliable Uncertainty Quantification in Large Language Models ACL 2026 Efficient Confidence Set Enumeration for Multi-label Conformal Classification UAI 2026 Efficient Federated Conformal Prediction with Group-Conditional Guarantee UAI 2026 Efficient Self-Evaluation for Diffusion Language Models via Sequence Regeneration ACL 2026 Eigenvalue Calibration for Semantic Embeddings of Large Language Models UAI 2026 Energy Waveify and Redistribution for Test-Time Adaptation: A Control System Perspective CVPR 2026 EpiCaR: Knowing What You Don’t Know Matters for Better Reasoning in LLMs ACL 2026 Estimating the Black-box LLM Uncertainty with Distribution-Aligned Adversarial Distillation ACL 2026 Every Response Counts: Quantifying Uncertainty of LLM-based Multi-Agent Systems through Tensor Decomposition ACL 2026 Evidential Deep Partial Label Learning to Quantify Disambiguation Uncertainty CVPR 2026