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Uncertainty in Language Models: Assessment through Rank-Calibration

Uncertainty in Language Models: Assessment through Rank-Calibration

4 April 2024
Xinmeng Huang
Shuo Li
Mengxin Yu
Matteo Sesia
Hamed Hassani
Insup Lee
Osbert Bastani
Edgar Dobriban
ArXivPDFHTML

Papers citing "Uncertainty in Language Models: Assessment through Rank-Calibration"

7 / 7 papers shown
Title
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
79
0
0
25 Apr 2025
What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering
What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering
Federico Errica
G. Siracusano
D. Sanvito
Roberto Bifulco
67
19
0
18 Jun 2024
One-Shot Safety Alignment for Large Language Models via Optimal
  Dualization
One-Shot Safety Alignment for Large Language Models via Optimal Dualization
Xinmeng Huang
Shuo Li
Edgar Dobriban
Osbert Bastani
Hamed Hassani
Dongsheng Ding
33
3
0
29 May 2024
Re-Examining Calibration: The Case of Question Answering
Re-Examining Calibration: The Case of Question Answering
Chenglei Si
Chen Zhao
Sewon Min
Jordan L. Boyd-Graber
41
30
0
25 May 2022
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLM
ALM
301
11,730
0
04 Mar 2022
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
268
5,635
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
247
9,042
0
06 Jun 2015
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