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Successive Prompting for Decomposing Complex Questions.

, , , и . EMNLP, стр. 1251-1265. Association for Computational Linguistics, (2022)

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CMU-LTI at KBP 2015 Event Track., , , , и . TAC, NIST, (2015)Tricks for Training Sparse Translation Models., , , , , и . NAACL-HLT, стр. 3340-3345. Association for Computational Linguistics, (2022)Benefits of Intermediate Annotations in Reading Comprehension., , и . ACL, стр. 5627-5634. Association for Computational Linguistics, (2020)Generating Natural Adversarial Examples., , и . CoRR, (2017)To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answering., , , и . CoRR, (2022)Evaluating Models' Local Decision Boundaries via Contrast Sets., , , , , , , , , и 16 other автор(ы). EMNLP (Findings), том EMNLP 2020 из Findings of ACL, стр. 1307-1323. Association for Computational Linguistics, (2020)Evaluating NLP Models via Contrast Sets., , , , , , , , , и 16 other автор(ы). CoRR, (2020)UCI Machine Learning Repository, и . (2017)DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs., , , , , и . NAACL-HLT (1), стр. 2368-2378. Association for Computational Linguistics, (2019)Comprehensive Multi-Dataset Evaluation of Reading Comprehension., , , , и . MRQA@EMNLP, стр. 147-153. Association for Computational Linguistics, (2019)