Mitigating Bias in Calibration Error Estimation

15 December 2020

Papers citing "Mitigating Bias in Calibration Error Estimation"

28 / 28 papers shown

Title
Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Review Toghrul Abbasli Kentaroh Toyoda Yuan Wang Leon Witt Muhammad Asif Ali Yukai Miao Dan Li Qingsong Wei UQCV 92 0 0 25 Apr 2025
MBCT: Tree-Based Feature-Aware Binning for Individual Uncertainty Calibration Siguang Huang Yunli Wang Lili Mou Huayue Zhang Han Zhu Chuan Yu Bo Zheng 60 15 0 13 Mar 2025
Optimizing Estimators of Squared Calibration Errors in Classification Sebastian G. Gruber Francis Bach 74 1 0 24 Feb 2025
Understanding the Capabilities and Limitations of Weak-to-Strong Generalization Wei Yao Wenkai Yang ziqi wang Yankai Lin Yong Liu ELM 105 1 0 03 Feb 2025
Rethinking Early Stopping: Refine, Then Calibrate Eugene Berta David Holzmüller Michael I. Jordan Francis Bach 67 0 0 31 Jan 2025
Combining Priors with Experience: Confidence Calibration Based on Binomial Process Modeling Jinzong Dong Zhaohui Jiang Dong Pan Haoyang Yu 56 0 0 14 Dec 2024
Calibrating Expressions of Certainty Peiqi Wang Barbara D. Lam Yingcheng Liu Ameneh Asgari-Targhi Rameswar Panda W. Wells Tina Kapur Polina Golland 32 1 0 06 Oct 2024
LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs Do Xuan Long Hai Nguyen Ngoc Tiviatis Sim Hieu Dao Shafiq R. Joty Kenji Kawaguchi Nancy F. Chen Min-Yen Kan 34 7 0 16 Aug 2024
Reassessing How to Compare and Improve the Calibration of Machine Learning Models M. Chidambaram Rong Ge 68 1 0 06 Jun 2024
Model Calibration in Dense Classification with Adaptive Label Perturbation Jiawei Liu Changkun Ye Shanpeng Wang Rui-Qing Cui Jing Zhang Kai Zhang Nick Barnes 47 5 0 25 Jul 2023
Set Learning for Accurate and Calibrated Models Lukas Muttenthaler Robert A. Vandermeulen Qiuyi Zhang Thomas Unterthiner Klaus-Robert Muller 31 2 0 05 Jul 2023
Dual Focal Loss for Calibration Linwei Tao Minjing Dong Chang Xu UQCV 39 26 0 23 May 2023
Minimum-Risk Recalibration of Classifiers Zeyu Sun Dogyoon Song Alfred Hero 30 5 0 18 May 2023
Calibration Error Estimation Using Fuzzy Binning Geetanjali Bihani Julia Taylor Rayz 95 2 0 30 Apr 2023
Calibrating a Deep Neural Network with Its Predecessors Linwei Tao Minjing Dong Daochang Liu Changming Sun Chang Xu BDL UQCV 12 5 0 13 Feb 2023
Evaluating Probabilistic Classifiers: The Triptych Timo Dimitriadis T. Gneiting Alexander I. Jordan Peter Vogel UQCV 23 10 0 25 Jan 2023
Annealing Double-Head: An Architecture for Online Calibration of Deep Neural Networks Erdong Guo D. Draper Maria de Iorio 35 0 0 27 Dec 2022
A Unifying Theory of Distance from Calibration Jarosław Błasiok Parikshit Gopalan Lunjia Hu Preetum Nakkiran 31 32 0 30 Nov 2022
AdaFocal: Calibration-aware Adaptive Focal Loss Arindam Ghosh Thomas Schaaf Matthew R. Gormley FedML UQCV 21 25 0 21 Nov 2022
Calibrated Selective Classification Adam Fisch Tommi Jaakkola Regina Barzilay 26 16 0 25 Aug 2022
Sample-dependent Adaptive Temperature Scaling for Improved Calibration Thomas Joy Francesco Pinto Ser-Nam Lim Philip H. S. Torr P. Dokania UQCV 27 30 0 13 Jul 2022
On the Usefulness of the Fit-on-the-Test View on Evaluating Calibration of Classifiers Markus Kängsepp Kaspar Valk Meelis Kull 27 3 0 16 Mar 2022
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time Mitchell Wortsman Gabriel Ilharco S. Gadre Rebecca Roelofs Raphael Gontijo-Lopes ... Hongseok Namkoong Ali Farhadi Y. Carmon Simon Kornblith Ludwig Schmidt MoMe 54 914 1 10 Mar 2022
T-Cal: An optimal test for the calibration of predictive models Donghwan Lee Xinmeng Huang Hamed Hassani Edgar Dobriban 22 20 0 03 Mar 2022
No One Representation to Rule Them All: Overlapping Features of Training Methods Raphael Gontijo-Lopes Yann N. Dauphin E. D. Cubuk 20 60 0 20 Oct 2021
Distribution-free calibration guarantees for histogram binning without sample splitting Chirag Gupta Aaditya Ramdas 19 37 0 10 May 2021
von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning Tyler R. Scott Andrew C. Gallagher Michael C. Mozer 25 38 0 29 Mar 2021
Improving model calibration with accuracy versus uncertainty optimization R. Krishnan Omesh Tickoo UQCV 188 157 0 14 Dec 2020