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LUQ: Long-text Uncertainty Quantification for LLMs

LUQ: Long-text Uncertainty Quantification for LLMs

29 March 2024
Caiqi Zhang
Fangyu Liu
Marco Basaldella
Nigel Collier
    HILM
ArXivPDFHTML

Papers citing "LUQ: Long-text Uncertainty Quantification for LLMs"

10 / 10 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
Calibrating Verbal Uncertainty as a Linear Feature to Reduce Hallucinations
Calibrating Verbal Uncertainty as a Linear Feature to Reduce Hallucinations
Ziwei Ji
L. Yu
Yeskendir Koishekenov
Yejin Bang
Anthony Hartshorn
Alan Schelten
Cheng Zhang
Pascale Fung
Nicola Cancedda
41
1
0
18 Mar 2025
Uncertainty Distillation: Teaching Language Models to Express Semantic Confidence
Uncertainty Distillation: Teaching Language Models to Express Semantic Confidence
Sophia Hager
David Mueller
Kevin Duh
Nicholas Andrews
59
0
0
18 Mar 2025
Integrative Decoding: Improve Factuality via Implicit Self-consistency
Integrative Decoding: Improve Factuality via Implicit Self-consistency
Yi Cheng
Xiao Liang
Yeyun Gong
Wen Xiao
Song Wang
...
Wenjie Li
Jian Jiao
Qi Chen
Peng Cheng
Wayne Xiong
HILM
43
1
0
02 Oct 2024
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph
Roman Vashurin
Ekaterina Fadeeva
Artem Vazhentsev
Akim Tsvigun
Daniil Vasilev
...
Timothy Baldwin
Timothy Baldwin
Maxim Panov
Artem Shelmanov
Artem Shelmanov
HILM
51
7
0
21 Jun 2024
Quantifying Uncertainty in Answers from any Language Model and Enhancing
  their Trustworthiness
Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness
Jiuhai Chen
Jonas W. Mueller
42
24
0
30 Aug 2023
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
159
86
0
10 Oct 2022
Reducing conversational agents' overconfidence through linguistic
  calibration
Reducing conversational agents' overconfidence through linguistic calibration
Sabrina J. Mielke
Arthur Szlam
Emily Dinan
Y-Lan Boureau
193
108
0
30 Dec 2020
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
243
9,042
0
06 Jun 2015
1