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Uncertainty-aware Language Modeling for Selective Question Answering

Uncertainty-aware Language Modeling for Selective Question Answering

26 November 2023
Qi Yang
Shreya Ravikumar
F. Schmitt-Ulms
S. Lolla
Ege Demir
I. Elistratov
Alex Lavaee
Sadhana Lolla
Elaheh Ahmadi
Daniela Rus
Alexander Amini
Alejandro Perez
ArXiv (abs)PDFHTML

Papers citing "Uncertainty-aware Language Modeling for Selective Question Answering"

16 / 16 papers shown
Title
SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step
  Reasoning
SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning
Ning Miao
Yee Whye Teh
Tom Rainforth
ReLMLRM
57
135
0
01 Aug 2023
Improving the repeatability of deep learning models with Monte Carlo
  dropout
Improving the repeatability of deep learning models with Monte Carlo dropout
A. Lemay
K. Hoebel
Christopher P. Bridge
B. Befano
Silvia De Sanjosé
Diden Egemen
A. Rodriguez
M. Schiffman
John Peter Campbell
Jayashree Kalpathy-Cramer
OOD
73
46
0
15 Feb 2022
A Survey on Automated Fact-Checking
A Survey on Automated Fact-Checking
Zhijiang Guo
Michael Schlichtkrull
Andreas Vlachos
92
495
0
26 Aug 2021
How Can We Know When Language Models Know? On the Calibration of
  Language Models for Question Answering
How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answering
Zhengbao Jiang
Jun Araki
Haibo Ding
Graham Neubig
UQCV
60
436
0
02 Dec 2020
Selective Question Answering under Domain Shift
Selective Question Answering under Domain Shift
Amita Kamath
Robin Jia
Percy Liang
OOD
54
212
0
16 Jun 2020
Posing Fair Generalization Tasks for Natural Language Inference
Posing Fair Generalization Tasks for Natural Language Inference
Atticus Geiger
Ignacio Cases
L. Karttunen
Christopher Potts
65
48
0
03 Nov 2019
NeMo: a toolkit for building AI applications using Neural Modules
NeMo: a toolkit for building AI applications using Neural Modules
Oleksii Kuchaiev
Jason Chun Lok Li
Huyen Nguyen
Oleksii Hrinchuk
Ryan Leary
...
Jack Cook
P. Castonguay
Mariya Popova
Jocelyn Huang
Jonathan M. Cohen
257
308
0
14 Sep 2019
DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep
  Networks
DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep Networks
Aryan Mobiny
H. Nguyen
S. Moulik
Naveen Garg
Carol C. Wu
UQCVBDL
60
161
0
07 Jun 2019
Know What You Don't Know: Unanswerable Questions for SQuAD
Know What You Don't Know: Unanswerable Questions for SQuAD
Pranav Rajpurkar
Robin Jia
Percy Liang
RALMELM
292
2,853
0
11 Jun 2018
Confidence Modeling for Neural Semantic Parsing
Confidence Modeling for Neural Semantic Parsing
Li Dong
Chris Quirk
Mirella Lapata
75
84
0
11 May 2018
On Calibration of Modern Neural Networks
On Calibration of Modern Neural Networks
Chuan Guo
Geoff Pleiss
Yu Sun
Kilian Q. Weinberger
UQCV
299
5,871
0
14 Jun 2017
Selective Classification for Deep Neural Networks
Selective Classification for Deep Neural Networks
Yonatan Geifman
Ran El-Yaniv
CVBM
97
530
0
23 May 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
UQCVBDL
842
5,841
0
05 Dec 2016
SQuAD: 100,000+ Questions for Machine Comprehension of Text
SQuAD: 100,000+ Questions for Machine Comprehension of Text
Pranav Rajpurkar
Jian Zhang
Konstantin Lopyrev
Percy Liang
RALM
316
8,174
0
16 Jun 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
UQCVBDL
856
9,353
0
06 Jun 2015
Deep Gaussian Processes
Deep Gaussian Processes
Andreas C. Damianou
Neil D. Lawrence
GPBDL
149
1,184
0
02 Nov 2012
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