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Does Self-Rationalization Improve Robustness to Spurious Correlations?

, , and . EMNLP, page 7403-7416. Association for Computational Linguistics, (2022)

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Learning Models for Actionable Recourse., , and . NeurIPS, page 18734-18746. (2021)Ensuring Actionable Recourse via Adversarial Training., , and . CoRR, (2020)How well do NLI models capture verb veridicality?, and . EMNLP/IJCNLP (1), page 2230-2240. Association for Computational Linguistics, (2019)Tailor: Generating and Perturbing Text with Semantic Controls., , , , and . ACL (1), page 3194-3213. Association for Computational Linguistics, (2022)Explaining NLP Models via Minimal Contrastive Editing (MiCE)., , and . CoRR, (2020)Competency Problems: On Finding and Removing Artifacts in Language Data., , , , , , and . EMNLP (1), page 1801-1813. Association for Computational Linguistics, (2021)Explaining NLP Models via Minimal Contrastive Editing (MiCE)., , and . ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 3840-3852. Association for Computational Linguistics, (2021)CREST: A Joint Framework for Rationalization and Counterfactual Text Generation., , , and . ACL (1), page 15109-15126. Association for Computational Linguistics, (2023)Language Modeling with Editable External Knowledge., , , , , and . CoRR, (2024)Probing What Different NLP Tasks Teach Machines about Function Word Comprehension., , , , , , , , , and 2 other author(s). CoRR, (2019)