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Scalable and accurate deep learning for electronic health records., , , , , , , , , and 24 other author(s). CoRR, (2018)Investigating Efficiently Extending Transformers for Long Input Summarization., , and . CoRR, (2022)Scalable and accurate deep learning with electronic health records., , , , , , , , , and 25 other author(s). npj Digit. Medicine, (2018)Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer, , , , , , , , and . (October 2019)cite arxiv:1910.10683.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)Online and Linear-Time Attention by Enforcing Monotonic Alignments., , , , and . ICML, volume 70 of Proceedings of Machine Learning Research, page 2837-2846. PMLR, (2017)PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization, , , and . (2019)SMART: Sentences as Basic Units for Text Evaluation., , , and . CoRR, (2022)Get To The Point: Summarization with Pointer-Generator Networks., , and . ACL (1), page 1073-1083. Association for Computational Linguistics, (2017)