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The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets.

, , and . AAAI, page 13180-13188. AAAI Press, (2021)

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Identifying Linear Relational Concepts in Large Language Models., , and . CoRR, (2023)SPARSEFIT: Few-shot Prompting with Sparse Fine-tuning for Jointly Generating Predictions and Natural Language Explanations., , and . CoRR, (2023)A Surprisingly Robust Trick for the Winograd Schema Challenge., , , , and . ACL (1), page 4837-4842. Association for Computational Linguistics, (2019)SparseFit: Few-shot Prompting with Sparse Fine-tuning for Jointly Generating Predictions and Natural Language Explanations., , , and . ACL (1), page 2053-2077. Association for Computational Linguistics, (2024)Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations., , , , and . ACL, page 4157-4165. Association for Computational Linguistics, (2020)Logical Reasoning for Natural Language Inference Using Generated Facts as Atoms., , , , and . CoRR, (2023)Towards Explainable and Trustworthy Autonomous Physical Systems., , , , , and . CHI Extended Abstracts, page 88:1-88:3. ACM, (2021)Using Natural Language Explanations to Improve Robustness of In-context Learning for Natural Language Inference., , , , and . CoRR, (2023)Using Natural Language Explanations to Improve Robustness of In-context Learning., , , , and . ACL (1), page 13477-13499. Association for Computational Linguistics, (2024)The Gap on GAP: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets., , and . CoRR, (2020)