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A Close Look into the Calibration of Pre-trained Language Models

A Close Look into the Calibration of Pre-trained Language Models

31 October 2022
Yangyi Chen
Lifan Yuan
Ganqu Cui
Zhiyuan Liu
Heng Ji
ArXivPDFHTML

Papers citing "A Close Look into the Calibration of Pre-trained Language Models"

26 / 26 papers shown
Title
Restoring Calibration for Aligned Large Language Models: A Calibration-Aware Fine-Tuning Approach
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
35
0
0
04 May 2025
Always Tell Me The Odds: Fine-grained Conditional Probability Estimation
Always Tell Me The Odds: Fine-grained Conditional Probability Estimation
Liaoyaqi Wang
Zhengping Jiang
Anqi Liu
Benjamin Van Durme
61
0
0
02 May 2025
MAC-Tuning: LLM Multi-Compositional Problem Reasoning with Enhanced Knowledge Boundary Awareness
MAC-Tuning: LLM Multi-Compositional Problem Reasoning with Enhanced Knowledge Boundary Awareness
Junsheng Huang
Zhitao He
Sandeep Polisetty
Q. Wang
May Fung
KELM
45
0
0
30 Apr 2025
Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Review
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
Large Language Model Confidence Estimation via Black-Box Access
Large Language Model Confidence Estimation via Black-Box Access
Tejaswini Pedapati
Amit Dhurandhar
Soumya Ghosh
Soham Dan
P. Sattigeri
89
3
0
21 Feb 2025
Understanding the Capabilities and Limitations of Weak-to-Strong Generalization
Understanding the Capabilities and Limitations of Weak-to-Strong Generalization
Wei Yao
Wenkai Yang
Zhilin Wang
Yankai Lin
Yong Liu
ELM
107
1
0
03 Feb 2025
Confidence Calibration of Classifiers with Many Classes
Confidence Calibration of Classifiers with Many Classes
Adrien LeCoz
Stéphane Herbin
Faouzi Adjed
UQCV
37
1
0
05 Nov 2024
On Calibration of LLM-based Guard Models for Reliable Content Moderation
On Calibration of LLM-based Guard Models for Reliable Content Moderation
Hongfu Liu
Hengguan Huang
Hao Wang
Xiangming Gu
Ye Wang
55
2
0
14 Oct 2024
Learning to Maximize Mutual Information for Chain-of-Thought
  Distillation
Learning to Maximize Mutual Information for Chain-of-Thought Distillation
Xin Chen
Hanxian Huang
Yanjun Gao
Yi Wang
Jishen Zhao
Ke Ding
35
11
0
05 Mar 2024
Calibrating Large Language Models with Sample Consistency
Calibrating Large Language Models with Sample Consistency
Qing Lyu
Kumar Shridhar
Chaitanya Malaviya
Li Zhang
Yanai Elazar
Niket Tandon
Marianna Apidianaki
Mrinmaya Sachan
Chris Callison-Burch
43
23
0
21 Feb 2024
Learning Shortcuts: On the Misleading Promise of NLU in Language Models
Learning Shortcuts: On the Misleading Promise of NLU in Language Models
Geetanjali Bihani
Julia Taylor Rayz
33
3
0
17 Jan 2024
Measuring and Improving Chain-of-Thought Reasoning in Vision-Language
  Models
Measuring and Improving Chain-of-Thought Reasoning in Vision-Language Models
Yangyi Chen
Karan Sikka
Michael Cogswell
Heng Ji
Ajay Divakaran
LRM
36
24
0
08 Sep 2023
Cognitive Architectures for Language Agents
Cognitive Architectures for Language Agents
T. Sumers
Shunyu Yao
Karthik Narasimhan
Thomas L. Griffiths
LLMAG
LM&Ro
54
153
0
05 Sep 2023
Revisiting Out-of-distribution Robustness in NLP: Benchmark, Analysis,
  and LLMs Evaluations
Revisiting Out-of-distribution Robustness in NLP: Benchmark, Analysis, and LLMs Evaluations
Lifan Yuan
Yangyi Chen
Ganqu Cui
Hongcheng Gao
Fangyuan Zou
Xingyi Cheng
Heng Ji
Zhiyuan Liu
Maosong Sun
39
73
0
07 Jun 2023
Taking Advice from ChatGPT
Taking Advice from ChatGPT
Peter Zhang
37
5
0
11 May 2023
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the
  Impact of Method & Data Scarcity
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity
Dennis Ulmer
J. Frellsen
Christian Hardmeier
189
22
0
20 Oct 2022
Uncertainty Quantification with Pre-trained Language Models: A
  Large-Scale Empirical Analysis
Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis
Yuxin Xiao
Paul Pu Liang
Umang Bhatt
W. Neiswanger
Ruslan Salakhutdinov
Louis-Philippe Morency
175
86
0
10 Oct 2022
Identifying and Mitigating Spurious Correlations for Improving
  Robustness in NLP Models
Identifying and Mitigating Spurious Correlations for Improving Robustness in NLP Models
Tianlu Wang
Rohit Sridhar
Diyi Yang
Xuezhi Wang
AAML
120
72
0
14 Oct 2021
Latent Hatred: A Benchmark for Understanding Implicit Hate Speech
Latent Hatred: A Benchmark for Understanding Implicit Hate Speech
Mai Elsherief
Caleb Ziems
D. Muchlinski
Vaishnavi Anupindi
Jordyn Seybolt
M. D. Choudhury
Diyi Yang
103
236
0
11 Sep 2021
The Power of Scale for Parameter-Efficient Prompt Tuning
The Power of Scale for Parameter-Efficient Prompt Tuning
Brian Lester
Rami Al-Rfou
Noah Constant
VPVLM
280
3,848
0
18 Apr 2021
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label
  Selection Framework for Semi-Supervised Learning
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
Mamshad Nayeem Rizve
Kevin Duarte
Y. S. Rawat
M. Shah
241
509
0
15 Jan 2021
DynaSent: A Dynamic Benchmark for Sentiment Analysis
DynaSent: A Dynamic Benchmark for Sentiment Analysis
Christopher Potts
Zhengxuan Wu
Atticus Geiger
Douwe Kiela
230
77
0
30 Dec 2020
Calibration of Pre-trained Transformers
Calibration of Pre-trained Transformers
Shrey Desai
Greg Durrett
UQLM
243
289
0
17 Mar 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
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
297
6,959
0
20 Apr 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,661
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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