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Does Putting a Linguist in the Loop Improve NLU Data Collection?

, , , , , , , , , and . EMNLP (Findings), page 4886-4901. Association for Computational Linguistics, (2021)

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A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference., , and . NAACL-HLT, page 1112-1122. Association for Computational Linguistics, (2018)Common Law Annotations: Investigating the Stability of Dialog System Output Annotations., , , , , , , , , and 2 other author(s). ACL (Findings), page 12315-12349. Association for Computational Linguistics, (2023)SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems., , , , , , , and . NeurIPS, page 3261-3275. (2019)What Ingredients Make for an Effective Crowdsourcing Protocol for Difficult NLU Data Collection Tasks?, , , , , and . ACL/IJCNLP (1), page 1221-1235. Association for Computational Linguistics, (2021)Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models., , , , , , , , , and 440 other author(s). CoRR, (2022)Discrete Latent Structure in Neural Networks., , , , and . CoRR, (2023)BBQ: A hand-built bias benchmark for question answering., , , , , , , and . ACL (Findings), page 2086-2105. Association for Computational Linguistics, (2022)What Makes Reading Comprehension Questions Difficult?, , , and . ACL (1), page 6951-6971. Association for Computational Linguistics, (2022)Human vs. Muppet: A Conservative Estimate of Human Performance on the GLUE Benchmark., and . ACL (1), page 4566-4575. Association for Computational Linguistics, (2019)Natural Language Understanding with the Quora Question Pairs Dataset, , , and . (2019)cite arxiv:1907.01041.