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Learning the Difference that Makes a Difference with
  Counterfactually-Augmented Data
v1v2 (latest)

Learning the Difference that Makes a Difference with Counterfactually-Augmented Data

International Conference on Learning Representations (ICLR), 2019
26 September 2019
Divyansh Kaushik
Eduard H. Hovy
Zachary Chase Lipton
    CML
ArXiv (abs)PDFHTML

Papers citing "Learning the Difference that Makes a Difference with Counterfactually-Augmented Data"

50 / 429 papers shown
When Does Syntax Mediate Neural Language Model Performance? Evidence
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Tiwalayo Eisape
Peng Qian
R. Levy
J. Shah
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145
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0
20 Apr 2022
Towards Fine-grained Causal Reasoning and QA
Towards Fine-grained Causal Reasoning and QA
Linyi Yang
Zhen Wang
Yuxiang Wu
Jie Yang
Yue Zhang
206
19
0
15 Apr 2022
VALUE: Understanding Dialect Disparity in NLU
VALUE: Understanding Dialect Disparity in NLUAnnual Meeting of the Association for Computational Linguistics (ACL), 2022
Caleb Ziems
Jiaao Chen
Camille Harris
J. Anderson
Diyi Yang
ELM
290
53
0
06 Apr 2022
Last Layer Re-Training is Sufficient for Robustness to Spurious
  Correlations
Last Layer Re-Training is Sufficient for Robustness to Spurious CorrelationsInternational Conference on Learning Representations (ICLR), 2022
Polina Kirichenko
Pavel Izmailov
A. Wilson
OOD
426
423
0
06 Apr 2022
Fact Checking with Insufficient Evidence
Fact Checking with Insufficient EvidenceTransactions of the Association for Computational Linguistics (TACL), 2022
Pepa Atanasova
J. Simonsen
Christina Lioma
Isabelle Augenstein
301
18
0
05 Apr 2022
A Rationale-Centric Framework for Human-in-the-loop Machine Learning
A Rationale-Centric Framework for Human-in-the-loop Machine LearningAnnual Meeting of the Association for Computational Linguistics (ACL), 2022
Jinghui Lu
Linyi Yang
Brian Mac Namee
Yue Zhang
228
43
0
24 Mar 2022
Text Transformations in Contrastive Self-Supervised Learning: A Review
Text Transformations in Contrastive Self-Supervised Learning: A ReviewInternational Joint Conference on Artificial Intelligence (IJCAI), 2022
Amrita Bhattacharjee
Mansooreh Karami
Huan Liu
SSL
381
23
0
22 Mar 2022
Out-of-distribution Generalization with Causal Invariant Transformations
Out-of-distribution Generalization with Causal Invariant TransformationsComputer Vision and Pattern Recognition (CVPR), 2022
Ruoyu Wang
Mingyang Yi
Zhitang Chen
Shengyu Zhu
OODOODD
256
79
0
22 Mar 2022
Leveraging Expert Guided Adversarial Augmentation For Improving
  Generalization in Named Entity Recognition
Leveraging Expert Guided Adversarial Augmentation For Improving Generalization in Named Entity RecognitionFindings (Findings), 2022
Aaron Reich
Jiaao Chen
Aastha Agrawal
Yanzhe Zhang
Diyi Yang
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218
6
0
21 Mar 2022
When Chosen Wisely, More Data Is What You Need: A Universal
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When Chosen Wisely, More Data Is What You Need: A Universal Sample-Efficient Strategy For Data AugmentationFindings (Findings), 2022
Ehsan Kamalloo
Mehdi Rezagholizadeh
A. Ghodsi
218
11
0
17 Mar 2022
Speaker Information Can Guide Models to Better Inductive Biases: A Case
  Study On Predicting Code-Switching
Speaker Information Can Guide Models to Better Inductive Biases: A Case Study On Predicting Code-SwitchingAnnual Meeting of the Association for Computational Linguistics (ACL), 2022
Alissa Ostapenko
S. Wintner
Melinda Fricke
Yulia Tsvetkov
183
6
0
16 Mar 2022
A Proposal to Study "Is High Quality Data All We Need?"
A Proposal to Study "Is High Quality Data All We Need?"
Swaroop Mishra
Anjana Arunkumar
123
3
0
12 Mar 2022
Automatically Generating Counterfactuals for Relation Classification
Automatically Generating Counterfactuals for Relation Classification
Mi Zhang
T. Qian
Tingyu Zhang
CML
239
0
0
22 Feb 2022
Prediction Sensitivity: Continual Audit of Counterfactual Fairness in
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Prediction Sensitivity: Continual Audit of Counterfactual Fairness in Deployed Classifiers
Krystal Maughan
Ivoline C. Ngong
Joseph P. Near
156
2
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Gradient-guided Unsupervised Text Style Transfer via Contrastive
  Learning
Gradient-guided Unsupervised Text Style Transfer via Contrastive Learning
Cheng Fan
Ziao Li
Wei Wei
152
2
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23 Jan 2022
A Causal Lens for Controllable Text Generation
A Causal Lens for Controllable Text GenerationNeural Information Processing Systems (NeurIPS), 2022
Zhiting Hu
Erran L. Li
224
72
0
22 Jan 2022
CommonsenseQA 2.0: Exposing the Limits of AI through Gamification
CommonsenseQA 2.0: Exposing the Limits of AI through Gamification
Alon Talmor
Ori Yoran
Ronan Le Bras
Chandrasekhar Bhagavatula
Yoav Goldberg
Yejin Choi
Jonathan Berant
ELM
313
167
0
14 Jan 2022
Making a (Counterfactual) Difference One Rationale at a Time
Making a (Counterfactual) Difference One Rationale at a TimeNeural Information Processing Systems (NeurIPS), 2022
Michael J. Plyler
Michal Green
Min Chi
224
12
0
13 Jan 2022
Robust Natural Language Processing: Recent Advances, Challenges, and
  Future Directions
Robust Natural Language Processing: Recent Advances, Challenges, and Future DirectionsIEEE Access (IEEE Access), 2022
Marwan Omar
Soohyeon Choi
Daehun Nyang
David A. Mohaisen
244
76
0
03 Jan 2022
Explain, Edit, and Understand: Rethinking User Study Design for
  Evaluating Model Explanations
Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model ExplanationsAAAI Conference on Artificial Intelligence (AAAI), 2021
Siddhant Arora
Danish Pruthi
Norman M. Sadeh
William W. Cohen
Zachary Chase Lipton
Graham Neubig
FAtt
198
43
0
17 Dec 2021
Measure and Improve Robustness in NLP Models: A Survey
Measure and Improve Robustness in NLP Models: A Survey
Xuezhi Wang
Haohan Wang
Diyi Yang
542
159
0
15 Dec 2021
Unsupervised Editing for Counterfactual Stories
Unsupervised Editing for Counterfactual Stories
Jiangjie Chen
Chun Gan
Sijie Cheng
Hao Zhou
Yanghua Xiao
Lei Li
280
12
0
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The Effect of Model Size on Worst-Group Generalization
The Effect of Model Size on Worst-Group Generalization
Alan Pham
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V. Srivatsa
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Yaoqing Yang
Yaodong Yu
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Joseph E. Gonzalez
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163
6
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08 Dec 2021
NL-Augmenter: A Framework for Task-Sensitive Natural Language
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NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole
Varun Gangal
Sebastian Gehrmann
Aadesh Gupta
Zhenhao Li
...
Tianbao Xie
Usama Yaseen
Michael A. Yee
J. Zhang
Yue Zhang
420
95
0
06 Dec 2021
LoNLI: An Extensible Framework for Testing Diverse Logical Reasoning
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LoNLI: An Extensible Framework for Testing Diverse Logical Reasoning Capabilities for NLILanguage Resources and Evaluation (LRE), 2021
Ishan Tarunesh
Somak Aditya
Monojit Choudhury
ELMLRM
183
4
0
04 Dec 2021
Editing a classifier by rewriting its prediction rules
Editing a classifier by rewriting its prediction rules
Shibani Santurkar
Dimitris Tsipras
Mahalaxmi Elango
David Bau
Antonio Torralba
Aleksander Madry
KELM
390
98
0
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Inducing Causal Structure for Interpretable Neural Networks
Inducing Causal Structure for Interpretable Neural Networks
Atticus Geiger
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Hanson Lu
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Elisa Kreiss
Thomas Icard
Noah D. Goodman
Christopher Potts
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384
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01 Dec 2021
Towards Principled Disentanglement for Domain Generalization
Towards Principled Disentanglement for Domain GeneralizationComputer Vision and Pattern Recognition (CVPR), 2021
Hanlin Zhang
Yi-Fan Zhang
Weiyang Liu
Adrian Weller
Bernhard Schölkopf
Eric Xing
OOD
401
144
0
27 Nov 2021
Interpreting Language Models Through Knowledge Graph Extraction
Interpreting Language Models Through Knowledge Graph Extraction
Vinitra Swamy
Angelika Romanou
Martin Jaggi
168
22
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16 Nov 2021
"Will You Find These Shortcuts?" A Protocol for Evaluating the
  Faithfulness of Input Salience Methods for Text Classification
"Will You Find These Shortcuts?" A Protocol for Evaluating the Faithfulness of Input Salience Methods for Text ClassificationConference on Empirical Methods in Natural Language Processing (EMNLP), 2021
Jasmijn Bastings
Sebastian Ebert
Polina Zablotskaia
Anders Sandholm
Katja Filippova
331
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NATURE: Natural Auxiliary Text Utterances for Realistic Spoken Language
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David Alfonso-Hermelo
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Huawei Noah’s
Mehdi Rezagholizadeh
262
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CLLD: Contrastive Learning with Label Distance for Text Classification
CLLD: Contrastive Learning with Label Distance for Text Classification
Jinhe Lan
Qingyuan Zhan
Chenhao Jiang
Kunping Yuan
Desheng Wang
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160
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25 Oct 2021
Fast Model Editing at Scale
Fast Model Editing at ScaleInternational Conference on Learning Representations (ICLR), 2021
E. Mitchell
Charles Lin
Antoine Bosselut
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Quantifying the Task-Specific Information in Text-Based Classifications
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Analyzing Dynamic Adversarial Training Data in the Limit
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Retrieval-guided Counterfactual Generation for QA
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Practical Benefits of Feature Feedback Under Distribution Shift
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Influence Tuning: Demoting Spurious Correlations via Instance
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Adversarial Examples Generation for Reducing Implicit Gender Bias in
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Enhancing Model Robustness and Fairness with Causality: A Regularization
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Counterfactual Adversarial Learning with Representation Interpolation
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Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning
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