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Learning Models for Actionable Recourse., , and . NeurIPS, page 18734-18746. (2021)Probing What Different NLP Tasks Teach Machines about Function Word Comprehension., , , , , , , , , and 2 other author(s). CoRR, (2019)Probing What Different NLP Tasks Teach Machines about Function Word Comprehension., , , , , , , , , and 2 other author(s). *SEM@NAACL-HLT, page 235-249. Association for Computational Linguistics, (2019)Does Self-Rationalization Improve Robustness to Spurious Correlations?, , and . EMNLP, page 7403-7416. Association for Computational Linguistics, (2022)Ensuring Actionable Recourse via Adversarial Training., , and . CoRR, (2020)Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks., , , , , , , , and . CoRR, (2023)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)Inverse Scaling: When Bigger Isn't Better., , , , , , , , , and 17 other author(s). CoRR, (2023)