probability estimation

BIRD: A Trustworthy Bayesian Inference Framework for Large Language Models ICLR 2025 Estimating LLM Consistency: A User Baseline vs Surrogate Metrics EMNLP 2025 Minimal Pair-Based Evaluation of Code-Switching ACL 2025 Specializing Large Language Models to Simulate Survey Response Distributions for Global Populations NAACL 2025 StoC-TOT: Stochastic Tree-of-Thought with Constrained Decoding for Complex Reasoning in Multi-Hop Question Answering NAACL 2025 CONTESTS: a Framework for Consistency Testing of Span Probabilities in Language Models EMNLP 2024 Do Neural Language Models Inferentially Compose Concepts the Way Humans Can? COLING 2024 MaxEnt Loss: Calibrating Graph Neural Networks under Out-of-Distribution Shift (Student Abstract) AAAI 2024 Pareto Optimal Learning for Estimating Large Language Model Errors ACL 2024 Towards Calibrated Multi-label Deep Neural Networks CVPR 2024 UMB: Understanding Model Behavior for Open-World Object Detection NeurIPS 2024 Where is the signal in tokenization space? EMNLP 2024 Probing neural language models for understanding of words of estimative probability ACL 2023 TCE: A Test-Based Approach to Measuring Calibration Error UAI 2023 The Geometry and Calculus of Losses JMLR 2023 Calibration of Machine Reading Systems at Scale ACL 2022 Deep Probability Estimation ICML 2022 Evaluating Distributional Distortion in Neural Language Modeling ICLR 2022 Stop Measuring Calibration When Humans Disagree EMNLP 2022 A statistical perspective on distillation ICML 2021 Calibration of Neural Networks using Splines ICLR 2021 Fenchel-Young Losses with Skewed Entropies for Class-posterior Probability Estimation AISTATS 2021 Iterative Connecting Probability Estimation for Networks NeurIPS 2021 On Focal Loss for Class-Posterior Probability Estimation: A Theoretical Perspective CVPR 2021 Random Forests for Opponent Hand Estimation in Gin Rummy AAAI 2021