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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"

12 / 12 papers shown
Title
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
65
0
0
18 Mar 2025
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
173
86
0
10 Oct 2022
Paradigm Shift in Natural Language Processing
Paradigm Shift in Natural Language Processing
Tianxiang Sun
Xiangyang Liu
Xipeng Qiu
Xuanjing Huang
116
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
27
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
209
97
0
14 Sep 2021
Uncertainty-Aware Reliable Text Classification
Uncertainty-Aware Reliable Text Classification
Yibo Hu
Latifur Khan
EDL
UQCV
25
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
182
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
104
180
0
19 Oct 2020
Calibration of Pre-trained Transformers
Calibration of Pre-trained Transformers
Shrey Desai
Greg Durrett
UQLM
243
289
0
17 Mar 2020
Six Challenges for Neural Machine Translation
Six Challenges for Neural Machine Translation
Philipp Koehn
Rebecca Knowles
AAML
AIMat
210
1,207
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
268
5,652
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
9,109
0
06 Jun 2015
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