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Finetuned Language Models are Zero-Shot Learners., , , , , , , , and . ICLR, OpenReview.net, (2022)Good-Enough Example Extrapolation.. EMNLP (1), page 5923-5929. Association for Computational Linguistics, (2021)Rationale-Augmented Ensembles in Language Models., , , , , and . CoRR, (2022)Transcending Scaling Laws with 0.1% Extra Compute., , , , , , , , , and 6 other author(s). EMNLP, page 1471-1486. Association for Computational Linguistics, (2023)UL2: Unifying Language Learning Paradigms., , , , , , , , , and 3 other author(s). ICLR, OpenReview.net, (2023)Text Augmentation in a Multi-Task View., , , and . EACL, page 2888-2894. Association for Computational Linguistics, (2021)Finding a Needle in the Haystack: Attention-Based Classification of High Resolution Microscopy Images., , , , , and . CoRR, (2018)A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity., , , , , , , , , and 1 other author(s). CoRR, (2023)Finetuned Language Models Are Zero-Shot Learners., , , , , , , , and . CoRR, (2021)Calibrating Histopathology Image Classifiers Using Label Smoothing., , , and . AIME, volume 13263 of Lecture Notes in Computer Science, page 273-282. Springer, (2022)