probability calibration

Grammar-Aligned Decoding NeurIPS 2024 I Don't Know: Explicit Modeling of Uncertainty with an [IDK] Token NeurIPS 2024 Perceptions of Linguistic Uncertainty by Language Models and Humans EMNLP 2024 Truthfulness of Calibration Measures NeurIPS 2024 Beyond probability partitions: Calibrating neural networks with semantic aware grouping NeurIPS 2023 Calibration by Distribution Matching: Trainable Kernel Calibration Metrics NeurIPS 2023 In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer NeurIPS 2023 Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback EMNLP 2023 Minimum-Risk Recalibration of Classifiers NeurIPS 2023 NCTV: Neural Clamping Toolkit and Visualization for Neural Network Calibration AAAI 2023 On the Calibration of Probabilistic Classifier Sets AISTATS 2023 Predicting Customer Satisfaction with Soft Labels for Ordinal Classification ACL 2023 Probability Guided Loss for Long-Tailed Multi-Label Image Classification AAAI 2023 RainProof: An Umbrella to Shield Text Generator from Out-Of-Distribution Data EMNLP 2023 Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks ICLR 2023 Unleashing the Multilingual Encoder Potential: Boosting Zero-Shot Performance via Probability Calibration EMNLP 2023 What Comes Next? Evaluating Uncertainty in Neural Text Generators Against Human Production Variability EMNLP 2023 A geometric method for improved uncertainty estimation in real-time UAI 2022 Answer-level Calibration for Free-form Multiple Choice Question Answering ACL 2022 Calibrating Deep Neural Networks by Pairwise Constraints CVPR 2022 Obtaining Calibrated Probabilities with Personalized Ranking Models AAAI 2022 Platt-Bin: Efficient Posterior Calibrated Training for NLP Classifiers ACL 2022 Top-label calibration and multiclass-to-binary reductions ICLR 2022 Towards Improving Selective Prediction Ability of NLP Systems ACL 2022 Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration NeurIPS 2021