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Finetuned Language Models are Zero-Shot Learners., , , , , , , , и . ICLR, OpenReview.net, (2022)Good-Enough Example Extrapolation.. EMNLP (1), стр. 5923-5929. Association for Computational Linguistics, (2021)Rationale-Augmented Ensembles in Language Models., , , , , и . CoRR, (2022)Transcending Scaling Laws with 0.1% Extra Compute., , , , , , , , , и 6 other автор(ы). EMNLP, стр. 1471-1486. Association for Computational Linguistics, (2023)Text Augmentation in a Multi-Task View., , , и . EACL, стр. 2888-2894. Association for Computational Linguistics, (2021)UL2: Unifying Language Learning Paradigms., , , , , , , , , и 3 other автор(ы). ICLR, OpenReview.net, (2023)Large Language Models Encode Clinical Knowledge., , , , , , , , , и 20 other автор(ы). CoRR, (2022)A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity., , , , , , , , , и 1 other автор(ы). CoRR, (2023)Finetuned Language Models Are Zero-Shot Learners., , , , , , , , и . CoRR, (2021)Calibrating Histopathology Image Classifiers Using Label Smoothing., , , и . AIME, том 13263 из Lecture Notes in Computer Science, стр. 273-282. Springer, (2022)