Explaining The Efficacy of Counterfactually Augmented Data

5 October 2020

Divyansh Kaushik

Amrith Rajagopal Setlur

Papers citing "Explaining The Efficacy of Counterfactually Augmented Data"

22 / 22 papers shown

Title
ACCORD: Closing the Commonsense Measurability Gap François Roewer-Després Jinyue Feng Zining Zhu Frank Rudzicz LRM 34 0 0 04 Jun 2024
Data Augmentations for Improved (Large) Language Model Generalization Amir Feder Yoav Wald Claudia Shi S. Saria David M. Blei OOD CML 21 7 0 19 Oct 2023
Out-of-Distribution Generalization in Text Classification: Past, Present, and Future Linyi Yang Y. Song Xuan Ren Chenyang Lyu Yidong Wang Lingqiao Liu Jindong Wang Jennifer Foster Yue Zhang OOD 20 2 0 23 May 2023
Learning to Generalize for Cross-domain QA Yingjie Niu Linyi Yang Ruihai Dong Yue Zhang 11 6 0 14 May 2023
GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective Linyi Yang Shuibai Zhang Libo Qin Yafu Li Yidong Wang Hanmeng Liu Jindong Wang Xingxu Xie Yue Zhang ELM 31 79 0 15 Nov 2022
NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer Data Augmentation Phillip Howard Gadi Singer Vasudev Lal Yejin Choi Swabha Swayamdipta CML 50 25 0 22 Oct 2022
Robustifying Sentiment Classification by Maximally Exploiting Few Counterfactuals Maarten De Raedt Fréderic Godin Chris Develder Thomas Demeester 6 1 0 21 Oct 2022
On Feature Learning in the Presence of Spurious Correlations Pavel Izmailov Polina Kirichenko Nate Gruver A. Wilson 24 116 0 20 Oct 2022
FactMix: Using a Few Labeled In-domain Examples to Generalize to Cross-domain Named Entity Recognition Linyi Yang Lifan Yuan Leyang Cui Wen Gao Yue Zhang 16 15 0 24 Aug 2022
Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models Esma Balkir S. Kiritchenko I. Nejadgholi Kathleen C. Fraser 16 36 0 08 Jun 2022
Necessity and Sufficiency for Explaining Text Classifiers: A Case Study in Hate Speech Detection Esma Balkir I. Nejadgholi Kathleen C. Fraser S. Kiritchenko FAtt 33 27 0 06 May 2022
Informativeness and Invariance: Two Perspectives on Spurious Correlations in Natural Language Jacob Eisenstein CML 26 25 0 09 Apr 2022
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations Polina Kirichenko Pavel Izmailov A. Wilson OOD 29 314 0 06 Apr 2022
A Rationale-Centric Framework for Human-in-the-loop Machine Learning Jinghui Lu Linyi Yang Brian Mac Namee Yue Zhang 8 39 0 24 Mar 2022
Diffusion Causal Models for Counterfactual Estimation Pedro Sanchez Sotirios A. Tsaftaris DiffM BDL 19 67 0 21 Feb 2022
Making a (Counterfactual) Difference One Rationale at a Time Michael J. Plyler Michal Green Min Chi 16 10 0 13 Jan 2022
An Investigation of the (In)effectiveness of Counterfactually Augmented Data Nitish Joshi He He OODD 19 46 0 01 Jul 2021
On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Study Divyansh Kaushik Douwe Kiela Zachary Chase Lipton Wen-tau Yih AAML 6 36 0 02 Jun 2021
Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests Victor Veitch Alexander DÁmour Steve Yadlowsky Jacob Eisenstein OOD 16 91 0 31 May 2021
A Survey of Data Augmentation Approaches for NLP Steven Y. Feng Varun Gangal Jason W. Wei Sarath Chandar Soroush Vosoughi Teruko Mitamura Eduard H. Hovy AIMat 32 796 0 07 May 2021
Hypothesis Only Baselines in Natural Language Inference Adam Poliak Jason Naradowsky Aparajita Haldar Rachel Rudinger Benjamin Van Durme 190 576 0 02 May 2018
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks Mohit Iyyer John Wieting Kevin Gimpel Luke Zettlemoyer AAML GAN 185 711 0 17 Apr 2018