Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis

10 October 2022

Papers citing "Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis"

9 / 9 papers shown

Title
Restoring Calibration for Aligned Large Language Models: A Calibration-Aware Fine-Tuning Approach Jiancong Xiao Bojian Hou Zhanliang Wang Ruochen Jin Q. Long Weijie Su Li Shen 10 0 0 04 May 2025
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 61 0 0 25 Apr 2025
Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates Dan Ley Umang Bhatt Adrian Weller UQCV 138 15 0 05 Dec 2021
Improving model calibration with accuracy versus uncertainty optimization R. Krishnan Omesh Tickoo UQCV 166 140 0 14 Dec 2020
Pre-trained Models for Natural Language Processing: A Survey Xipeng Qiu Tianxiang Sun Yige Xu Yunfan Shao Ning Dai Xuanjing Huang LM&MA VLM 217 1,281 0 18 Mar 2020
Calibration of Pre-trained Transformers Shrey Desai Greg Durrett UQLM 216 245 0 17 Mar 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 283 6,003 0 20 Apr 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 265 4,940 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 237 8,157 0 06 Jun 2015