Calibration

When is Multicalibration Post-Processing Necessary? NeurIPS 2024 Distributionally Robust Ensemble of Lottery Tickets Towards Calibrated Sparse Network Training NeurIPS 2023 Preserving Pre-trained Features Helps Calibrate Fine-tuned Language Models ICLR 2023 The Fine Print on Tempered Posteriors ACML 2023 Transferable Post-hoc Calibration on Pretrained Transformers in Noisy Text Classification AAAI 2023 U-Calibration: Forecasting for an Unknown Agent COLT 2023 DALE: Differential Accumulated Local Effects for efficient and accurate global explanations ACML 2022 Faster online calibration without randomization: interval forecasts and the power of two choices COLT 2022 Low-Degree Multicalibration COLT 2022 On the Calibration of Massively Multilingual Language Models EMNLP 2022 Out of Distribution Detection via Neural Network Anchoring ACML 2022 Improving Calibration through the Relationship with Adversarial Robustness NeurIPS 2021 On the Effects of Transformer Size on In- and Out-of-Domain Calibration EMNLP 2021 Probability Calibration for Knowledge Graph Embedding Models ICLR 2020 Selective Question Answering under Domain Shift ACL 2020 Calibrated Structured Prediction NeurIPS 2015 Large-scale probabilistic predictors with and without guarantees of validity NeurIPS 2015