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BARACK: Partially Supervised Group Robustness With Guarantees, , , , , , and . arXiv preprint arXiv:2201.00072, (2021)COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation., , , , , , , and . CoRR, (2022)UniREx: A Unified Learning Framework for Language Model Rationale Extraction., , , , , , , and . CoRR, (2021)FRAME: Evaluating Simulatability Metrics for Free-Text Rationales., , , , , , and . CoRR, (2022)Feature Selection for Facebook Feed Ranking System via a Group-Sparsity-Regularized Training Algorithm., , , , , , and . CIKM, page 2085-2088. ACM, (2019)ER-TEST: Evaluating Explanation Regularization Methods for NLP Models., , , , , , and . CoRR, (2022)Are Machine Rationales (Not) Useful to Humans? Measuring and Improving Human Utility of Free-text Rationales., , , , , , , , and . ACL (1), page 7103-7128. Association for Computational Linguistics, (2023)Visualizing Deep Neural Networks for Text Analytics., , , , , , , and . PacificVis, page 180-189. IEEE Computer Society, (2018)APrompt: Attention Prompt Tuning for Efficient Adaptation of Pre-trained Language Models., , , , , , , , , and 1 other author(s). EMNLP, page 9147-9160. Association for Computational Linguistics, (2023)COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation., , , , , , , and . EMNLP, page 13258-13275. Association for Computational Linguistics, (2023)