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Pretraining Language Models with Human Preferences.

, , , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 17506-17533. PMLR, (2023)

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Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks., , and . CoRR, (2018)What Do NLP Researchers Believe? Results of the NLP Community Metasurvey., , , , , , , , , and 1 other author(s). CoRR, (2022)An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization., , , , , , , , , and 1 other author(s). CoRR, (2020)Globally-Aware Multiple Instance Classifier for Breast Cancer Screening., , , , , , , and . MLMI@MICCAI, volume 11861 of Lecture Notes in Computer Science, page 18-26. Springer, (2019)Pretraining Language Models with Human Preferences., , , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 17506-17533. PMLR, (2023)What Do NLP Researchers Believe? Results of the NLP Community Metasurvey., , , , , , , , , and 1 other author(s). ACL (1), page 16334-16368. Association for Computational Linguistics, (2023)Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models., , , , , , , , , and 440 other author(s). Trans. Mach. Learn. Res., (2023)Investigating Efficiently Extending Transformers for Long Input Summarization., , and . CoRR, (2022)Unsupervised Sentence Compression using Denoising Auto-Encoders., and . CoNLL, page 413-422. Association for Computational Linguistics, (2018)Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models., , , , , , , , , and 440 other author(s). CoRR, (2022)