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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer, , , , , , , , and . (October 2019)cite arxiv:1910.10683.Investigating Efficiently Extending Transformers for Long Input Summarization., , and . CoRR, (2022)Scalable and accurate deep learning for electronic health records., , , , , , , , , and 24 other author(s). CoRR, (2018)Scalable and accurate deep learning with electronic health records., , , , , , , , , and 25 other author(s). npj Digit. Medicine, (2018)Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models., , , , , , , , , and 31 other author(s). Trans. Mach. Learn. Res., (2024)Statistical Rejection Sampling Improves Preference Optimization., , , , , , and . ICLR, OpenReview.net, (2024)Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer., , , , , , , , and . J. Mach. Learn. Res., (2020)Unsupervised Pretraining for Sequence to Sequence Learning., , and . EMNLP, page 383-391. Association for Computational Linguistics, (2017)PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization., , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 11328-11339. PMLR, (2020)Small-scale proxies for large-scale Transformer training instabilities., , , , , , , , , and 6 other author(s). ICLR, OpenReview.net, (2024)