"model calibration" Papers
30 papers found
Conference
Calibrating LLMs with Information-Theoretic Evidential Deep Learning
Yawei Li, David Rügamer, Bernd Bischl et al.
Confidence Elicitation: A New Attack Vector for Large Language Models
Brian Formento, Chuan Sheng Foo, See-Kiong Ng
Confidence Estimation for Error Detection in Text-to-SQL Systems
Oleg Somov, Elena Tutubalina
Feature Clipping for Uncertainty Calibration
Linwei Tao, Minjing Dong, Chang Xu
HaDeMiF: Hallucination Detection and Mitigation in Large Language Models
Xiaoling Zhou, Mingjie Zhang, Zhemg Lee et al.
Mind the Uncertainty in Human Disagreement: Evaluating Discrepancies Between Model Predictions and Human Responses in VQA
Jian Lan, Diego Frassinelli, Barbara Plank
NeuralSurv: Deep Survival Analysis with Bayesian Uncertainty Quantification
Mélodie Monod, Alessandro Micheli, Samir Bhatt
Performative Risk Control: Calibrating Models for Reliable Deployment under Performativity
Victor Li, Baiting Chen, Yuzhen Mao et al.
Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function
Linlin Yu, Bowen Yang, Tianhao Wang et al.
SteerConf: Steering LLMs for Confidence Elicitation
Ziang Zhou, Tianyuan Jin, Jieming Shi et al.
The Illusion of Progress? A Critical Look at Test-Time Adaptation for Vision-Language Models
Lijun Sheng, Jian Liang, Ran He et al.
Towards Certification of Uncertainty Calibration under Adversarial Attacks
Cornelius Emde, Francesco Pinto, Thomas Lukasiewicz et al.
Towards Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It
Guoxuan Xia, Olivier Laurent, Gianni Franchi et al.
Uncertainty Weighted Gradients for Model Calibration
Jinxu Lin, Linwei Tao, Minjing Dong et al.
Varying Shades of Wrong: Aligning LLMs with Wrong Answers Only
Jihan Yao, Wenxuan Ding, Shangbin Feng et al.
An Empirical Study Into What Matters for Calibrating Vision-Language Models
Weijie Tu, Weijian Deng, Dylan Campbell et al.
Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration
Shi-ang Qi, Yakun Yu, Russell Greiner
FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler
Hongyi Peng, Han Yu, Xiaoli Tang et al.
Flattening the Parent Bias: Hierarchical Semantic Segmentation in the Poincaré Ball
Simon Weber, Barış Zöngür, Nikita Araslanov et al.
How Flawed Is ECE? An Analysis via Logit Smoothing
Muthu Chidambaram, Holden Lee, Colin McSwiggen et al.
IW-GAE: Importance weighted group accuracy estimation for improved calibration and model selection in unsupervised domain adaptation
Taejong Joo, Diego Klabjan
Pseudo-Calibration: Improving Predictive Uncertainty Estimation in Unsupervised Domain Adaptation
Dapeng Hu, Jian Liang, Xinchao Wang et al.
Reliability in Semantic Segmentation: Can We Use Synthetic Data?
Thibaut Loiseau, Tuan Hung Vu, Mickael Chen et al.
Revisit the Essence of Distilling Knowledge through Calibration
Wen-Shu Fan, Su Lu, Xin-Chun Li et al.
Robust Calibration of Large Vision-Language Adapters
Balamurali Murugesan, Julio Silva-Rodríguez, Ismail Ben Ayed et al.
TEA: Test-time Energy Adaptation
Yige Yuan, Bingbing Xu, Liang Hou et al.
The Entropy Enigma: Success and Failure of Entropy Minimization
Ori Press, Ravid Shwartz-Ziv, Yann LeCun et al.
Thermometer: Towards Universal Calibration for Large Language Models
Maohao Shen, Subhro Das, Kristjan Greenewald et al.
ViT-Calibrator: Decision Stream Calibration for Vision Transformer
Lin Chen, Zhijie Jia, Lechao Cheng et al.
Watch Your Head: Assembling Projection Heads to Save the Reliability of Federated Models
Authors: Jinqian Chen, Jihua Zhu, Qinghai Zheng et al.