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Insertion Transformer: Flexible Sequence Generation via Insertion Operations.

, , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 5976-5985. PMLR, (2019)

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An Empirical Study of Generation Order for Machine Translation., , , and . CoRR, (2019)Insertion Transformer: Flexible Sequence Generation via Insertion Operations., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 5976-5985. PMLR, (2019)Generate, Annotate, and Learn: Generative Models Advance Self-Training and Knowledge Distillation., , , , and . CoRR, (2021)Multichannel Generative Language Model: Learning All Possible Factorizations Within and Across Channels., , and . EMNLP (Findings), volume EMNLP 2020 of Findings of ACL, page 4208-4220. Association for Computational Linguistics, (2020)Generate, Annotate, and Learn: NLP with Synthetic Text., , , , and . Trans. Assoc. Comput. Linguistics, (2022)ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning., , , , and . CoRR, (2019)Modular Length Control for Sentence Generation., , , and . ESANN, page 607-612. (2020)DOM-Q-NET: Grounded RL on Structured Language., , and . ICLR (Poster), OpenReview.net, (2019)Contextual Lensing of Universal Sentence Representations.. CoRR, (2020)Improving domain adaptation in de-identification of electronic health records through self-training., , , , and . J. Am. Medical Informatics Assoc., 28 (10): 2093-2100 (2021)