post-hoc calibration

MINDS at SemEval-2026-Task 13: Robust Detection of Machine-Generated Code under Distribution Shift SemEval 2026 Instance-Wise Monotonic Calibration by Constrained Transformation UAI 2025 Page Stream Segmentation with LLMs: Challenges and Applications in Insurance Document Automation COLING 2025 PC-GZSL: Prior Correction for Generalized Zero Shot Learning WACV 2025 A Benchmark Study on Calibration ICLR 2024 Calibration Bottleneck: Over-compressed Representations are Less Calibratable ICML 2024 Distance-aware Calibration for Pre-trained Language Models EMNLP 2024 QuantProb: Generalizing Probabilities along with Predictions for a Pre-trained Classifier UAI 2024 On the Pitfall of Mixup for Uncertainty Calibration CVPR 2023 Scaling of Class-wise Training Losses for Post-hoc Calibration ICML 2023 T-Cal: An Optimal Test for the Calibration of Predictive Models JMLR 2023 Test Time Augmentation Meets Post-hoc Calibration: Uncertainty Quantification under Real-World Conditions AAAI 2023 VRA: Variational Rectified Activation for Out-of-distribution Detection NeurIPS 2023 A geometric method for improved uncertainty estimation in real-time UAI 2022 Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration NeurIPS 2021 Improving uncertainty calibration of deep neural networks via truth discovery and geometric optimization UAI 2021 Meta-Cal: Well-controlled Post-hoc Calibration by Ranking ICML 2021 Post-Hoc Uncertainty Calibration for Domain Drift Scenarios CVPR 2021 Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence NeurIPS 2021 Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks NeurIPS 2020