🔗 Who cites «Counterfactually-Augmented SNLI Training Data Does Not Yield Better Generalization Than Unaugmented Data»

18 papers of our library cite it (of the 141,840 whose bibliographies we read) · 2 with a page here, the most cited first · ← back to «Counterfactually-Augmented SNLI Training Data Does Not Yield Better Generalization Than Unaugmented Data»

1. Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving ModelsTongshuang Wu, Marco Tulio Ribeiro, Jeffrey Heer, et al.2021 · 272 citations
2. Measure and Improve Robustness in NLP Models: A SurveyXuezhi Wang, Haohan Wang, Diyi Yang2022 · 148 citations

16 more papers of our library cite it; they have no page here yet.

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