Bayesian Inference

Prediction-Powered Adaptive Shrinkage Estimation ICML 2025 Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function ICLR 2025 Prior2Former - Evidential Modeling of Mask Transformers for Assumption-Free Open-World Panoptic Segmentation ICCV 2025 Prior2Posterior: Model Prior Correction for Long-Tailed Learning WACV 2025 Prior-Dependent Allocations for Bayesian Fixed-Budget Best-Arm Identification in Structured Bandits AISTATS 2025 Probabilistic Inertial Poser (ProbIP): Uncertainty-aware Human Motion Modeling from Sparse Inertial Sensors ICCV 2025 Probabilistic Learning to Defer: Handling Missing Expert Annotations and Controlling Workload Distribution ICLR 2025 Probabilistic Soundness Guarantees in LLM Reasoning Chains EMNLP 2025 ProHOC: Probabilistic Hierarchical Out-of-Distribution Classification via Multi-Depth Networks CVPR 2025 Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models ICML 2025 ProPose: Probabilistic 3D Human Pose Estimation with Instance-Level Distribution and Normalizing Flow AAAI 2025 Provable Uncertainty Decomposition via Higher-Order Calibration ICLR 2025 QA-Calibration of Language Model Confidence Scores ICLR 2025 QPruner: Probabilistic Decision Quantization for Structured Pruning in Large Language Models NAACL 2025 Quantifying and Narrowing the Unknown: Interactive Text-to-Video Retrieval via Uncertainty Minimization ICCV 2025 Quantifying the Effectiveness of Linear Preconditioning in Markov Chain Monte Carlo JMLR 2025 Quantitative Predictive Monitoring and Control for Safe Human-Machine Interaction AAAI 2025 Quantized Can Still Be Calibrated: A Unified Framework to Calibration in Quantized Large Language Models ACL 2025 QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions ICML 2025 Questioning Our Questions: How Well Do Medical QA Benchmarks Evaluate Clinical Capabilities of Language Models? ACL 2025 Rapid Mismatch Estimation via Neural Network Informed Variational Inference CoRL 2025 Rate-In: Information-Driven Adaptive Dropout Rates for Improved Inference-Time Uncertainty Estimation CVPR 2025 REALM: Recursive Relevance Modeling for LLM-based Document Re-Ranking EMNLP 2025 Reference-Based Post-OCR Processing with LLM for Precise Diacritic Text in Historical Document Recognition AAAI 2025 Regularized Best-of-N Sampling with Minimum Bayes Risk Objective for Language Model Alignment NAACL 2025