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Targeted Data Generation: Finding and Fixing Model Weaknesses.

, , and . ACL (1), page 8506-8520. Association for Computational Linguistics, (2023)

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Learning Robust Representations by Projecting Superficial Statistics Out., , , and . ICLR, OpenReview.net, (2019)Leashing the Inner Demons: Self-Detoxification for Language Models., , , and . AAAI, page 11530-11537. AAAI Press, (2022)Large Scale Knowledge Washing., , , , and . CoRR, (2024)InterFair: Debiasing with Natural Language Feedback for Fair Interpretable Predictions., , and . EMNLP, page 9466-9471. Association for Computational Linguistics, (2023)Leveraging Gloss Knowledge in Neural Word Sense Disambiguation by Hierarchical Co-Attention., , , , , and . EMNLP, page 1402-1411. Association for Computational Linguistics, (2018)Targeted Data Generation: Finding and Fixing Model Weaknesses., , and . ACL (1), page 8506-8520. Association for Computational Linguistics, (2023)LVCHAT: Facilitating Long Video Comprehension., , , and . CoRR, (2024)Robust and Interpretable Medical Image Classifiers via Concept Bottleneck Models., , , , , , , , , and 1 other author(s). CoRR, (2023)Synthetic Pre-Training Tasks for Neural Machine Translation., , , , and . ACL (Findings), page 8080-8098. Association for Computational Linguistics, (2023)Detect and Perturb: Neutral Rewriting of Biased and Sensitive Text via Gradient-based Decoding., , and . EMNLP (Findings), page 4173-4181. Association for Computational Linguistics, (2021)