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FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation.

, , , , , and . EMNLP (1), page 3712-3727. Association for Computational Linguistics, (2021)

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Towards Automatic Generation of Peer-Targeted Science Talk in Curiosity-Evoking Virtual Agent., , , , and . IVA, page 71-78. ACM, (2018)Entity Projection via Machine Translation for Cross-Lingual NER., , and . EMNLP/IJCNLP (1), page 1083-1092. Association for Computational Linguistics, (2019)QUASER: Question Answering with Scalable Extractive Rationalization., , , , , and . SIGIR, page 1208-1218. ACM, (2022)PuMer: Pruning and Merging Tokens for Efficient Vision Language Models., , and . ACL (1), page 12890-12903. Association for Computational Linguistics, (2023)Stop Clickbait: Detecting and preventing clickbaits in online news media., , , and . ASONAM, page 9-16. IEEE Computer Society, (2016)Husky: A Unified, Open-Source Language Agent for Multi-Step Reasoning., , , and . CoRR, (2024)Retrieval-guided Counterfactual Generation for QA., , and . ACL (1), page 1670-1686. Association for Computational Linguistics, (2022)Prompting Contrastive Explanations for Commonsense Reasoning Tasks., , , , and . ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 4179-4192. Association for Computational Linguistics, (2021)FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation., , , , , and . EMNLP (1), page 3712-3727. Association for Computational Linguistics, (2021)Contextualized Representations for Low-resource Utterance Tagging., and . SIGdial, page 68-74. Association for Computational Linguistics, (2019)