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Uncertainty in Natural Language Processing: Sources, Quantification, and
  Applications

Uncertainty in Natural Language Processing: Sources, Quantification, and Applications

5 June 2023
Mengting Hu
Zhen Zhang
Shiwan Zhao
Minlie Huang
Bingzhe Wu
    BDL
ArXivPDFHTML

Papers citing "Uncertainty in Natural Language Processing: Sources, Quantification, and Applications"

34 / 34 papers shown
Title
Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space
Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space
Zhen Zhang
Xuehai He
Weixiang Yan
Ao Shen
Chenyang Zhao
Shuaiqiang Wang
Yelong Shen
Xin Eric Wang
LRM
12
0
0
21 May 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
72
0
0
18 Mar 2025
Your Model is Overconfident, and Other Lies We Tell Ourselves
Timothee Mickus
Aman Sinha
Raúl Vázquez
60
0
0
03 Mar 2025
Embracing Diversity: A Multi-Perspective Approach with Soft Labels
Benedetta Muscato
Praveen Bushipaka
Gizem Gezici
Lucia Passaro
F. Giannotti
Tommaso Cucinotta
44
0
0
01 Mar 2025
Black-box Uncertainty Quantification Method for LLM-as-a-Judge
Black-box Uncertainty Quantification Method for LLM-as-a-Judge
Nico Wagner
Michael Desmond
Rahul Nair
Zahra Ashktorab
Elizabeth M. Daly
Qian Pan
Martin Santillan Cooper
James M. Johnson
Werner Geyer
ELM
UQCV
52
4
0
15 Oct 2024
Reference-free Hallucination Detection for Large Vision-Language Models
Reference-free Hallucination Detection for Large Vision-Language Models
Qing Li
Chenyang Lyu
Jiahui Geng
Derui Zhu
Maxim Panov
Fakhri Karray
32
6
0
11 Aug 2024
Question Rephrasing for Quantifying Uncertainty in Large Language
  Models: Applications in Molecular Chemistry Tasks
Question Rephrasing for Quantifying Uncertainty in Large Language Models: Applications in Molecular Chemistry Tasks
Zizhang Chen
Pengyu Hong
Sandeep Madireddy
37
1
0
07 Aug 2024
Survey and Taxonomy: The Role of Data-Centric AI in Transformer-Based
  Time Series Forecasting
Survey and Taxonomy: The Role of Data-Centric AI in Transformer-Based Time Series Forecasting
Jingjing Xu
Caesar Wu
Yuan-Fang Li
Grégoire Danoy
Pascal Bouvry
AI4TS
45
1
0
29 Jul 2024
Internal Consistency and Self-Feedback in Large Language Models: A
  Survey
Internal Consistency and Self-Feedback in Large Language Models: A Survey
Xun Liang
Shichao Song
Zifan Zheng
Hanyu Wang
Qingchen Yu
...
Rong-Hua Li
Peng Cheng
Zhonghao Wang
Zhiyu Li
Zhiyu Li
HILM
LRM
73
28
0
19 Jul 2024
Domain-specific or Uncertainty-aware models: Does it really make a
  difference for biomedical text classification?
Domain-specific or Uncertainty-aware models: Does it really make a difference for biomedical text classification?
Aman Sinha
Timothee Mickus
Marianne Clausel
Mathieu Constant
X. Coubez
47
0
0
17 Jul 2024
Uncertainty Quantification in Large Language Models Through Convex Hull
  Analysis
Uncertainty Quantification in Large Language Models Through Convex Hull Analysis
Ferhat Ozgur Catak
Murat Kuzlu
UQCV
62
4
0
28 Jun 2024
InternalInspector $I^2$: Robust Confidence Estimation in LLMs through
  Internal States
InternalInspector I2I^2I2: Robust Confidence Estimation in LLMs through Internal States
Mohammad Beigi
Ying Shen
Runing Yang
Zihao Lin
Qifan Wang
Ankith Mohan
Jianfeng He
Ming Jin
Chang-Tien Lu
Lifu Huang
HILM
36
4
0
17 Jun 2024
Semantic Density: Uncertainty Quantification in Semantic Space for Large
  Language Models
Semantic Density: Uncertainty Quantification in Semantic Space for Large Language Models
Xin Qiu
Risto Miikkulainen
54
3
0
22 May 2024
Conformal Prediction for Natural Language Processing: A Survey
Conformal Prediction for Natural Language Processing: A Survey
Margarida M. Campos
António Farinhas
Chrysoula Zerva
Mário A. T. Figueiredo
André F. T. Martins
AI4CE
54
15
0
03 May 2024
P-NAL: an Effective and Interpretable Entity Alignment Method
P-NAL: an Effective and Interpretable Entity Alignment Method
Chuanhao Xu
Jingwei Cheng
Fu Zhang
54
1
0
18 Apr 2024
Think Twice Before Trusting: Self-Detection for Large Language Models
  through Comprehensive Answer Reflection
Think Twice Before Trusting: Self-Detection for Large Language Models through Comprehensive Answer Reflection
Moxin Li
Wenjie Wang
Fuli Feng
Fengbin Zhu
Qifan Wang
Tat-Seng Chua
HILM
LRM
48
16
0
15 Mar 2024
LinkNER: Linking Local Named Entity Recognition Models to Large Language
  Models using Uncertainty
LinkNER: Linking Local Named Entity Recognition Models to Large Language Models using Uncertainty
Zhen Zhang
Yuhua Zhao
Hang Gao
Mengting Hu
37
21
0
16 Feb 2024
Calibrating Long-form Generations from Large Language Models
Calibrating Long-form Generations from Large Language Models
Yukun Huang
Yixin Liu
Raghuveer Thirukovalluru
Arman Cohan
Bhuwan Dhingra
27
7
0
09 Feb 2024
Benchmarking LLMs via Uncertainty Quantification
Benchmarking LLMs via Uncertainty Quantification
Fanghua Ye
Mingming Yang
Jianhui Pang
Longyue Wang
Derek F. Wong
Emine Yilmaz
Shuming Shi
Zhaopeng Tu
ELM
28
47
0
23 Jan 2024
Copy Suppression: Comprehensively Understanding an Attention Head
Copy Suppression: Comprehensively Understanding an Attention Head
Callum McDougall
Arthur Conmy
Cody Rushing
Thomas McGrath
Neel Nanda
MILM
25
42
0
06 Oct 2023
Uncertainty in Natural Language Generation: From Theory to Applications
Uncertainty in Natural Language Generation: From Theory to Applications
Joris Baan
Nico Daheim
Evgenia Ilia
Dennis Ulmer
Haau-Sing Li
Raquel Fernández
Barbara Plank
Rico Sennrich
Chrysoula Zerva
Wilker Aziz
UQLM
39
40
0
28 Jul 2023
Can Large Language Models Capture Dissenting Human Voices?
Can Large Language Models Capture Dissenting Human Voices?
Noah Lee
Na Min An
James Thorne
ALM
47
30
0
23 May 2023
Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large
  Language Models
Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language Models
Alfonso Amayuelas
Kyle Wong
Liangming Pan
Wenhu Chen
Wenjie Wang
42
25
0
23 May 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
Willie Neiswanger
Ruslan Salakhutdinov
Louis-Philippe Morency
175
87
0
10 Oct 2022
Paradigm Shift in Natural Language Processing
Paradigm Shift in Natural Language Processing
Tianxiang Sun
Xiangyang Liu
Xipeng Qiu
Xuanjing Huang
126
82
0
26 Sep 2021
Will this Question be Answered? Question Filtering via Answer Model
  Distillation for Efficient Question Answering
Will this Question be Answered? Question Filtering via Answer Model Distillation for Efficient Question Answering
Siddhant Garg
Alessandro Moschitti
29
26
0
14 Sep 2021
Types of Out-of-Distribution Texts and How to Detect Them
Types of Out-of-Distribution Texts and How to Detect Them
Udit Arora
William Huang
He He
OODD
225
97
0
14 Sep 2021
Uncertainty-Aware Reliable Text Classification
Uncertainty-Aware Reliable Text Classification
Yibo Hu
Latifur Khan
EDL
UQCV
38
33
0
15 Jul 2021
Consistent Accelerated Inference via Confident Adaptive Transformers
Consistent Accelerated Inference via Confident Adaptive Transformers
Tal Schuster
Adam Fisch
Tommi Jaakkola
Regina Barzilay
AI4TS
200
69
0
18 Apr 2021
Cold-start Active Learning through Self-supervised Language Modeling
Cold-start Active Learning through Self-supervised Language Modeling
Michelle Yuan
Hsuan-Tien Lin
Jordan L. Boyd-Graber
116
180
0
19 Oct 2020
Calibration of Pre-trained Transformers
Calibration of Pre-trained Transformers
Shrey Desai
Greg Durrett
UQLM
246
290
0
17 Mar 2020
Six Challenges for Neural Machine Translation
Six Challenges for Neural Machine Translation
Philipp Koehn
Rebecca Knowles
AAML
AIMat
227
1,211
0
12 Jun 2017
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
5,695
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
287
9,167
0
06 Jun 2015
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