Revisiting the Calibration of Modern Neural Networks

15 June 2021

Papers citing "Revisiting the Calibration of Modern Neural Networks"

50 / 254 papers shown

Title
On the Calibration of Multilingual Question Answering LLMs Yahan Yang Soham Dan Dan Roth Insup Lee 11 2 0 15 Nov 2023
A Saliency-based Clustering Framework for Identifying Aberrant Predictions A. Tersol Montserrat Alexander R. Loftus Yael Daihes 12 0 0 11 Nov 2023
Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks Ahmad Rashid Serena Hacker Guojun Zhang Agustinus Kristiadi Pascal Poupart OODD 33 0 0 07 Nov 2023
Towards Calibrated Robust Fine-Tuning of Vision-Language Models Changdae Oh Hyesu Lim Mijoo Kim Dongyoon Han Junhyeok Park Euiseog Jeong Alexander G. Hauptmann Zhi-Qi Cheng Kyungwoo Song VLM 27 13 0 03 Nov 2023
Understanding the Effects of Projectors in Knowledge Distillation Yudong Chen Sen Wang Jiajun Liu Xuwei Xu Frank de Hoog Brano Kusy Zi Huang 26 0 0 26 Oct 2023
MaxEnt Loss: Constrained Maximum Entropy for Calibration under Out-of-Distribution Shift Dexter Neo Stefan Winkler Tsuhan Chen OODD 22 3 0 26 Oct 2023
Hypernymy Understanding Evaluation of Text-to-Image Models via WordNet Hierarchy Anton Baryshnikov Max Ryabinin VLM 16 2 0 13 Oct 2023
Jointly-Learned Exit and Inference for a Dynamic Neural Network : JEI-DNN Florence Regol Joud Chataoui Mark J. Coates 29 6 0 13 Oct 2023
How (not) to ensemble LVLMs for VQA Lisa Alazraki Lluis Castrejon Mostafa Dehghani Fantine Huot J. Uijlings Thomas Mensink 35 3 0 10 Oct 2023
Deterministic Langevin Unconstrained Optimization with Normalizing Flows James M. Sullivan U. Seljak 24 0 0 01 Oct 2023
A Primer on Bayesian Neural Networks: Review and Debates Federico Danieli Konstantinos Pitas M. Vladimirova Vincent Fortuin BDL AAML 56 18 0 28 Sep 2023
Bayesian Personalized Federated Learning with Shared and Personalized Uncertainty Representations Hui Chen Hengyu Liu LongBing Cao Tiancheng Zhang FedML 47 3 0 27 Sep 2023
On Calibration of Modern Quantized Efficient Neural Networks Joe-Hwa Kuang Alexander Wong UQCV MQ 24 1 0 25 Sep 2023
Understanding Calibration of Deep Neural Networks for Medical Image Classification A. Sambyal Usma Niyaz N. C. Krishnan Deepti R. Bathula 17 7 0 22 Sep 2023
Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing Jarosław Błasiok Preetum Nakkiran UQCV 48 20 0 21 Sep 2023
You can have your ensemble and run it too -- Deep Ensembles Spread Over Time Isak Meding Alexander Bodin Adam Tonderski Joakim Johnander Christoffer Petersson Lennart Svensson OOD UQCV 15 1 0 20 Sep 2023
On the Efficacy of Multi-scale Data Samplers for Vision Applications Elvis Nunez Thomas Merth Anish K. Prabhu Mehrdad Farajtabar Mohammad Rastegari Sachin Mehta Maxwell Horton 23 1 0 08 Sep 2023
Distributionally Robust Statistical Verification with Imprecise Neural Networks Souradeep Dutta Michele Caprio Vivian Lin Matthew Cleaveland Kuk Jin Jang I. Ruchkin O. Sokolsky Insup Lee OOD AAML 49 7 0 28 Aug 2023
How Safe Am I Given What I See? Calibrated Prediction of Safety Chances for Image-Controlled Autonomy Zhenjiang Mao Carson Sobolewski I. Ruchkin 32 8 0 23 Aug 2023
ACLS: Adaptive and Conditional Label Smoothing for Network Calibration Hyekang Park Jongyoun Noh Youngmin Oh Donghyeon Baek Bumsub Ham UQCV 36 12 0 23 Aug 2023
A Benchmark Study on Calibration Linwei Tao Younan Zhu Haolan Guo Minjing Dong Chang Xu 21 9 0 23 Aug 2023
Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration Error Zixin Wang Yadan Luo Zhi Chen Sen Wang Zi Huang 27 11 0 06 Aug 2023
Calibration in Deep Learning: A Survey of the State-of-the-Art Cheng Wang UQCV 31 36 0 02 Aug 2023
Measuring and Modeling Uncertainty Degree for Monocular Depth Estimation Mochu Xiang Jing Zhang Nick Barnes Yuchao Dai UQCV 45 3 0 19 Jul 2023
Towards Reliable Rare Category Analysis on Graphs via Individual Calibration Longfeng Wu Bowen Lei Dongkuan Xu Dawei Zhou UQCV CML 36 9 0 19 Jul 2023
An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration Hiroki Naganuma Ryuichiro Hataya Kotaro Yoshida Ioannis Mitliagkas OODD 92 1 0 17 Jul 2023
Achelous: A Fast Unified Water-surface Panoptic Perception Framework based on Fusion of Monocular Camera and 4D mmWave Radar Runwei Guan Shanliang Yao Xiaohui Zhu Ka Lok Man Eng Gee Lim Jeremy S. Smith Yong 0001Yue Yutao Yue VOS 29 17 0 14 Jul 2023
Set Learning for Accurate and Calibrated Models Lukas Muttenthaler Robert A. Vandermeulen Qiuyi Zhang Thomas Unterthiner Klaus-Robert Muller 34 2 0 05 Jul 2023
TCE: A Test-Based Approach to Measuring Calibration Error Takuo Matsubara Niek Tax Richard Mudd Ido Guy 19 4 0 25 Jun 2023
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs Miao Xiong Zhiyuan Hu Xinyang Lu Yifei Li Jie Fu Junxian He Bryan Hooi 28 370 0 22 Jun 2023
Beyond Probability Partitions: Calibrating Neural Networks with Semantic Aware Grouping Jia-Qi Yang De-Chuan Zhan Le Gan UQCV 27 5 0 08 Jun 2023
Proximity-Informed Calibration for Deep Neural Networks Miao Xiong Ailin Deng Pang Wei Koh Jiaying Wu Shen Li Jianqing Xu Bryan Hooi UQCV 21 12 0 07 Jun 2023
When to Read Documents or QA History: On Unified and Selective Open-domain QA Kyungjae Lee Sanghyun Han Seung-won Hwang Moontae Lee RALM 24 4 0 07 Jun 2023
Deep neural networks architectures from the perspective of manifold learning German Magai AAML AI4CE 24 6 0 06 Jun 2023
A Large-Scale Study of Probabilistic Calibration in Neural Network Regression V. Dheur Souhaib Ben Taieb BDL 35 13 0 05 Jun 2023
A Data-Driven Measure of Relative Uncertainty for Misclassification Detection Eduardo Dadalto Camara Gomes Marco Romanelli Georg Pichler Pablo Piantanida UQCV 32 5 0 02 Jun 2023
Calibrating Multimodal Learning Huanrong Zhang Changqing Zhang Bing Wu Huazhu Fu Qiufeng Wang Q. Hu 59 16 0 02 Jun 2023
On the Limitations of Temperature Scaling for Distributions with Overlaps Muthuraman Chidambaram Rong Ge UQCV 37 4 0 01 Jun 2023
Probabilistic Uncertainty Quantification of Prediction Models with Application to Visual Localization Junan Chen Josephine Monica Wei-Lun Chao Mark E. Campbell 18 4 0 31 May 2023
When Does Optimizing a Proper Loss Yield Calibration? Jarosław Błasiok Parikshit Gopalan Lunjia Hu Preetum Nakkiran 36 23 0 30 May 2023
Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models Shuai Zhao Xiaohan Wang Linchao Zhu Yezhou Yang VLM 26 22 0 29 May 2023
Three Towers: Flexible Contrastive Learning with Pretrained Image Models Jannik Kossen Mark Collier Basil Mustafa Tianlin Li Xiaohua Zhai Lucas Beyer Andreas Steiner Jesse Berent Rodolphe Jenatton Efi Kokiopoulou VLM 42 11 0 26 May 2023
Utility-Probability Duality of Neural Networks Bojun Huang Fei Yuan UQCV 27 1 0 24 May 2023
Prompting is not a substitute for probability measurements in large language models Jennifer Hu R. Levy 33 38 0 22 May 2023
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing Zhibin Gou Zhihong Shao Yeyun Gong Yelong Shen Yujiu Yang Nan Duan Weizhu Chen KELM LRM 36 357 0 19 May 2023
Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement Ailin Deng Miao Xiong Bryan Hooi 41 6 0 02 May 2023
QuantProb: Generalizing Probabilities along with Predictions for a Pre-trained Classifier Aditya Challa Snehanshu Saha S. Dhavala UQCV 30 2 0 25 Apr 2023
Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness Bo Li Gexiang Fang Yang Yang Quansen Wang Wei Ye Wen Zhao Shikun Zhang ELM AI4MH 24 157 0 23 Apr 2023
Loss Minimization Yields Multicalibration for Large Neural Networks Jarosław Błasiok Parikshit Gopalan Lunjia Hu Adam Tauman Kalai Preetum Nakkiran FaML UQCV 43 10 0 19 Apr 2023
Revisiting Single-gated Mixtures of Experts Amelie Royer I. Karmanov Andrii Skliar B. Bejnordi Tijmen Blankevoort MoE MoMe 36 6 0 11 Apr 2023