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MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding.

, , , , , , , , , and . EMNLP, page 16369-16382. Association for Computational Linguistics, (2023)

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An Empirical Investigation of Representation Learning for Imitation., , , , , , , , , and 2 other author(s). CoRR, (2022)Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback., , , , , , , , , and 6 other author(s). NeurIPS (Competition and Demos), volume 176 of Proceedings of Machine Learning Research, page 259-272. PMLR, (2021)An Empirical Investigation of Representation Learning for Imitation., , , , , , , , , and 3 other author(s). NeurIPS Datasets and Benchmarks, (2021)The MineRL BASALT Competition on Learning from Human Feedback., , , , , , , , , and 3 other author(s). CoRR, (2021)Retrospective on the 2021 BASALT Competition on Learning from Human Feedback., , , , , , , , , and 6 other author(s). CoRR, (2022)imitation: Clean Imitation Learning Implementations., , , , , , , , , and . CoRR, (2022)MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding., , , , , , , , , and . EMNLP, page 16369-16382. Association for Computational Linguistics, (2023)