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Unlearn Dataset Bias in Natural Language Inference by Fitting the
  Residual

Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual

28 August 2019
He He
Sheng Zha
Haohan Wang
ArXivPDFHTML

Papers citing "Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual"

37 / 37 papers shown
Title
Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known
  Dataset Biases
Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases
Christopher Clark
Mark Yatskar
Luke Zettlemoyer
OOD
71
465
0
09 Sep 2019
On Adversarial Removal of Hypothesis-only Bias in Natural Language
  Inference
On Adversarial Removal of Hypothesis-only Bias in Natural Language Inference
Yonatan Belinkov
Adam Poliak
Stuart M. Shieber
Benjamin Van Durme
Alexander M. Rush
AAML
62
71
0
09 Jul 2019
Don't Take the Premise for Granted: Mitigating Artifacts in Natural
  Language Inference
Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference
Yonatan Belinkov
Adam Poliak
Stuart M. Shieber
Benjamin Van Durme
Alexander M. Rush
51
95
0
09 Jul 2019
HellaSwag: Can a Machine Really Finish Your Sentence?
HellaSwag: Can a Machine Really Finish Your Sentence?
Rowan Zellers
Ari Holtzman
Yonatan Bisk
Ali Farhadi
Yejin Choi
168
2,464
0
19 May 2019
Selection Bias Explorations and Debias Methods for Natural Language
  Sentence Matching Datasets
Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets
Guanhua Zhang
Bing Bai
Jian Liang
Kun Bai
Shiyu Chang
Mo Yu
Conghui Zhu
Tiejun Zhao
43
27
0
15 May 2019
Good-Enough Compositional Data Augmentation
Good-Enough Compositional Data Augmentation
Jacob Andreas
66
234
0
21 Apr 2019
Gender Bias in Contextualized Word Embeddings
Gender Bias in Contextualized Word Embeddings
Jieyu Zhao
Tianlu Wang
Mark Yatskar
Ryan Cotterell
Vicente Ordonez
Kai-Wei Chang
FaML
115
419
0
05 Apr 2019
Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets
Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets
Nelson F. Liu
Roy Schwartz
Noah A. Smith
AAML
66
106
0
04 Apr 2019
PAWS: Paraphrase Adversaries from Word Scrambling
PAWS: Paraphrase Adversaries from Word Scrambling
Yuan Zhang
Jason Baldridge
Luheng He
68
543
0
01 Apr 2019
Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases
  in Word Embeddings But do not Remove Them
Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
Hila Gonen
Yoav Goldberg
96
571
0
09 Mar 2019
Learning Robust Representations by Projecting Superficial Statistics Out
Learning Robust Representations by Projecting Superficial Statistics Out
Haohan Wang
Zexue He
Zachary Chase Lipton
Eric Xing
OOD
61
235
0
02 Mar 2019
Training on Synthetic Noise Improves Robustness to Natural Noise in
  Machine Translation
Training on Synthetic Noise Improves Robustness to Natural Noise in Machine Translation
Vladimir Karpukhin
Omer Levy
Jacob Eisenstein
Marjan Ghazvininejad
37
117
0
05 Feb 2019
Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural
  Language Inference
Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference
R. Thomas McCoy
Ellie Pavlick
Tal Linzen
129
1,237
0
04 Feb 2019
Theoretically Principled Trade-off between Robustness and Accuracy
Theoretically Principled Trade-off between Robustness and Accuracy
Hongyang R. Zhang
Yaodong Yu
Jiantao Jiao
Eric Xing
L. Ghaoui
Michael I. Jordan
129
2,548
0
24 Jan 2019
Learning Models with Uniform Performance via Distributionally Robust
  Optimization
Learning Models with Uniform Performance via Distributionally Robust Optimization
John C. Duchi
Hongseok Namkoong
OOD
55
418
0
20 Oct 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
VLM
SSL
SSeg
1.7K
94,729
0
11 Oct 2018
Learning Gender-Neutral Word Embeddings
Learning Gender-Neutral Word Embeddings
Jieyu Zhao
Yichao Zhou
Zeyu Li
Wei Wang
Kai-Wei Chang
FaML
91
412
0
29 Aug 2018
How Much Reading Does Reading Comprehension Require? A Critical
  Investigation of Popular Benchmarks
How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks
Divyansh Kaushik
Zachary Chase Lipton
ELM
67
232
0
14 Aug 2018
Stress Test Evaluation for Natural Language Inference
Stress Test Evaluation for Natural Language Inference
Aakanksha Naik
Abhilasha Ravichander
Norman M. Sadeh
Carolyn Rose
Graham Neubig
ELM
67
376
0
02 Jun 2018
Robustness May Be at Odds with Accuracy
Robustness May Be at Odds with Accuracy
Dimitris Tsipras
Shibani Santurkar
Logan Engstrom
Alexander Turner
Aleksander Madry
AAML
99
1,778
0
30 May 2018
Breaking NLI Systems with Sentences that Require Simple Lexical
  Inferences
Breaking NLI Systems with Sentences that Require Simple Lexical Inferences
Max Glockner
Vered Shwartz
Yoav Goldberg
NAI
72
366
0
06 May 2018
Hypothesis Only Baselines in Natural Language Inference
Hypothesis Only Baselines in Natural Language Inference
Adam Poliak
Jason Naradowsky
Aparajita Haldar
Rachel Rudinger
Benjamin Van Durme
229
579
0
02 May 2018
Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods
Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods
Jieyu Zhao
Tianlu Wang
Mark Yatskar
Vicente Ordonez
Kai-Wei Chang
115
932
0
18 Apr 2018
Annotation Artifacts in Natural Language Inference Data
Annotation Artifacts in Natural Language Inference Data
Suchin Gururangan
Swabha Swayamdipta
Omer Levy
Roy Schwartz
Samuel R. Bowman
Noah A. Smith
142
1,177
0
06 Mar 2018
Detecting and Correcting for Label Shift with Black Box Predictors
Detecting and Correcting for Label Shift with Black Box Predictors
Zachary Chase Lipton
Yu Wang
Alex Smola
OOD
58
553
0
12 Feb 2018
Men Also Like Shopping: Reducing Gender Bias Amplification using
  Corpus-level Constraints
Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints
Jieyu Zhao
Tianlu Wang
Mark Yatskar
Vicente Ordonez
Kai-Wei Chang
FaML
90
970
0
29 Jul 2017
Adversarial Examples for Evaluating Reading Comprehension Systems
Adversarial Examples for Evaluating Reading Comprehension Systems
Robin Jia
Percy Liang
AAML
ELM
196
1,605
0
23 Jul 2017
A Broad-Coverage Challenge Corpus for Sentence Understanding through
  Inference
A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
Adina Williams
Nikita Nangia
Samuel R. Bowman
517
4,476
0
18 Apr 2017
The Effect of Different Writing Tasks on Linguistic Style: A Case Study
  of the ROC Story Cloze Task
The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task
Roy Schwartz
Maarten Sap
Ioannis Konstas
Leila Zilles
Yejin Choi
Noah A. Smith
76
120
0
07 Feb 2017
Enhanced LSTM for Natural Language Inference
Enhanced LSTM for Natural Language Inference
Qian Chen
Xiao-Dan Zhu
Zhenhua Ling
Si Wei
Hui Jiang
Diana Inkpen
LRM
ReLM
94
1,129
0
20 Sep 2016
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word
  Embeddings
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
Tolga Bolukbasi
Kai-Wei Chang
James Zou
Venkatesh Saligrama
Adam Kalai
CVBM
FaML
105
3,133
0
21 Jul 2016
Analyzing the Behavior of Visual Question Answering Models
Analyzing the Behavior of Visual Question Answering Models
Aishwarya Agrawal
Dhruv Batra
Devi Parikh
73
312
0
23 Jun 2016
A Decomposable Attention Model for Natural Language Inference
A Decomposable Attention Model for Natural Language Inference
Ankur P. Parikh
Oscar Täckström
Dipanjan Das
Jakob Uszkoreit
337
1,374
0
06 Jun 2016
Natural Language Inference by Tree-Based Convolution and Heuristic
  Matching
Natural Language Inference by Tree-Based Convolution and Heuristic Matching
Lili Mou
Rui Men
Ge Li
Yan Xu
Lu Zhang
Rui Yan
Zhi Jin
75
353
0
28 Dec 2015
A large annotated corpus for learning natural language inference
A large annotated corpus for learning natural language inference
Samuel R. Bowman
Gabor Angeli
Christopher Potts
Christopher D. Manning
307
4,282
0
21 Aug 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.7K
150,006
0
22 Dec 2014
On Causal and Anticausal Learning
On Causal and Anticausal Learning
Bernhard Schölkopf
Dominik Janzing
J. Peters
Eleni Sgouritsa
Kun Zhang
Joris Mooij
CML
81
607
0
27 Jun 2012
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