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Counterfactual examples have proven to be valuable in the field of natural language processing (NLP) for both evaluating and improving the robustness of language models to spurious correlations in datasets.
Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, and David Lopez-Paz. 2019 · 1907
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Roberta: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Learning the difference that makes a difference with counterfactually-augmented data
Divyansh Kaushik, Eduard Hovy, and Zachary C Lipton. 2019 · 1909
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Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, and Jamie Brew. 2019 · 1910
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Shiori Sagawa, Pang Wei Koh, Tatsunori B Hashimoto, and Percy Liang. 2019 · 1911
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Evaluating models’ local decision boundaries via contrast sets
Matt Gardner, Yoav Artzi, Victoria Basmova, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, et al. 2020 · 2004
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Causal mediation analysis for interpreting neural nlp: The case of gender bias
Jesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Simas Sakenis, Jason Huang, Yaron Singer, and Stuart Shieber. 2020 · 2004
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Noise or signal: The role of image backgrounds in object recognition
Kai Xiao, Logan Engstrom, Andrew Ilyas, and Aleksander Madry. 2020 · 2006
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Natural language processing with Python: analyzing text with the natural language toolkit
Steven Bird, Ewan Klein, and Edward Loper. 2009 · 2009
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The winograd schema challenge
Hector Levesque, Ernest Davis, and Leora Morgenstern. 2012 · 2012
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick. 2014 · 2014
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Peter Young, Alice Lai, Micah Hodosh, and Julia Hockenmaier. 2014 · 2014
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang. 2015 · 2015
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Foil it! find one mismatch between image and language caption
Ravi Shekhar, Sandro Pezzelle, Yauhen Klimovich, Aurélie Herbelot, Moin Nabi, Enver Sangineto, and Raffaella Bernardi. 2017 · 2017
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2018 · 2018
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Shortcut learning in deep neural networks
Robert Geirhos, Jörn-Henrik Jacobsen, Claudio Michaelis, Richard Zemel, Wieland Brendel, Matthias Bethge, and Felix A Wichmann. 2020 · 2020
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Vilt: Vision-and-language transformer without convolution or region supervision
Wonjae Kim, Bokyung Son, and Ildoo Kim. 2021 · 2021
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen. 2021 · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021 · 2021
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2021 · 2021
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Salient imagenet: How to discover spurious features in deep learning?
An investigation of the (in) effectiveness of counterfactually augmented data
Nitish Joshi and He He. 2022 · 2022
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Compositional visual generation with composable diffusion models
Nan Liu, Shuang Li, Yilun Du, Antonio Torralba, and Joshua B Tenenbaum. 2022 · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen. 2022 · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al. 2022 · 2022
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FLAVA: A foundational language and vision alignment model
Amanpreet Singh, Ronghang Hu, Vedanuj Goswami, Guillaume Couairon, Wojciech Galuba, Marcus Rohrbach, and Douwe Kiela. 2022 · 2022
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Sahil Singla and Soheil Feizi. 2021 · 2021
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Robustness to spurious correlations in text classification via automatically generated counterfactuals
Zhao Wang and Aron Culotta. 2021 · 2021
Cited alongside, same era.
Polyjuice: Generating counterfactuals for explaining, evaluating, and improving models
Tongshuang Wu, Marco Tulio Ribeiro, Jeffrey Heer, and Daniel S Weld. 2021 · 2021
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Exploring the efficacy of automatically generated counterfactuals for sentiment analysis
Linyi Yang, Jiazheng Li, Padraig Cunningham, Yue Zhang, Barry Smyth, and Ruihai Dong. 2021 · 2021
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Docogen: Domain counterfactual generation for low resource domain adaptation
Nitay Calderon, Eyal Ben-David, Amir Feder, and Roi Reichart. 2022 · 2022
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Dall-eval: Probing the reasoning skills and social biases of text-to-image generative models
Jaemin Cho, Abhay Zala, and Mohit Bansal. 2022 · 2022
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Jacob Eisenstein. 2022 · 2022
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Causal inference in natural language processing: Estimation, prediction, interpretation and beyond
Amir Feder, Katherine A Keith, Emaad Manzoor, Reid Pryzant, Dhanya Sridhar, Zach Wood-Doughty, Jacob Eisenstein, Justin Grimmer, Roi Reichart, Margaret E Roberts, et al. 2022 · 2022
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Winoground: Probing vision and language models for visio-linguistic compositionality
Tristan Thrush, Ryan Jiang, Max Bartolo, Amanpreet Singh, Adina Williams, Douwe Kiela, and Candace Ross. 2022 · 2022
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Bridge-tower: Building bridges between encoders in vision-language representation learning
Xiao Xu, Chenfei Wu, Shachar Rosenman, Vasudev Lal, and Nan Duan. 2022 · 2022
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Easily accessible text-to-image generation amplifies demographic stereotypes at large scale
Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, and Aylin Caliskan. 2023 · 2023
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Stable bias: Analyzing societal representations in diffusion models
Alexandra Sasha Luccioni, Christopher Akiki, Margaret Mitchell, and Yacine Jernite. 2023 · 2023
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Spawrious: A benchmark for fine control of spurious correlation biases
Aengus Lynch, Gbètondji JS Dovonon, Jean Kaddour, and Ricardo Silva. 2023 · 2023
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It is all about where you start: Text-to-image generation with seed selection
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Effective data augmentation with diffusion models
Brandon Trabucco, Kyle Doherty, Max Gurinas, and Ruslan Salakhutdinov. 2023 · 2023
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Dataset interfaces: Diagnosing model failures using controllable counterfactual generation
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