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When Do You Need Billions of Words of Pretraining Data?, , , and . CoRR, (2020)Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks., , and . CoRR, (2018)The Capacity for Moral Self-Correction in Large Language Models., , , , , , , , , and 39 other author(s). CoRR, (2023)What Do NLP Researchers Believe? Results of the NLP Community Metasurvey., , , , , , , , , and 1 other author(s). CoRR, (2022)Probing What Different NLP Tasks Teach Machines about Function Word Comprehension., , , , , , , , , and 2 other author(s). CoRR, (2019)Probing What Different NLP Tasks Teach Machines about Function Word Comprehension., , , , , , , , , and 2 other author(s). *SEM@NAACL-HLT, page 235-249. Association for Computational Linguistics, (2019)Does Putting a Linguist in the Loop Improve NLU Data Collection?, , , , , , , , , and . EMNLP (Findings), page 4886-4901. Association for Computational Linguistics, (2021)Language Modeling Teaches You More than Translation Does: Lessons Learned Through Auxiliary Syntactic Task Analysis., and . BlackboxNLP@EMNLP, page 359-361. Association for Computational Linguistics, (2018)Pretraining Language Models with Human Preferences., , , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 17506-17533. PMLR, (2023)Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling., , , , , , , , , and 6 other author(s). ACL (1), page 4465-4476. Association for Computational Linguistics, (2019)