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Annotation Artifacts in Natural Language Inference Data.

, , , , , and . NAACL-HLT (2), page 107-112. Association for Computational Linguistics, (2018)

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Multi-Mention Learning for Reading Comprehension with Neural Cascades., , and . CoRR, (2017)Annotation Artifacts in Natural Language Inference Data., , , , , and . NAACL-HLT (2), page 107-112. Association for Computational Linguistics, (2018)Frame Semantics across Languages: Towards a Multilingual FrameNet., , , and . COLING (Tutorials), page 9-12. Association for Computational Linguistics, (2018)WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation., , , and . EMNLP (Findings), page 6826-6847. Association for Computational Linguistics, (2022)A Dependency Parser for Tweets., , , , , and . EMNLP, page 1001-1012. ACL, (2014)Multi-Mention Learning for Reading Comprehension with Neural Cascades., , and . ICLR (Poster), OpenReview.net, (2018)Investigating the Benefits of Free-Form Rationales., , , and . EMNLP (Findings), page 5867-5882. Association for Computational Linguistics, (2022)Polyglot Semantic Role Labeling., , and . ACL (2), page 667-672. Association for Computational Linguistics, (2018)Don't Stop Pretraining: Adapt Language Models to Domains and Tasks., , , , , , and . ACL, page 8342-8360. Association for Computational Linguistics, (2020)On-the-Fly Controlled Text Generation with Experts and Anti-Experts., , , , , , and . CoRR, (2021)