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Meta-Learning for Low-Resource Neural Machine Translation.

, , , , and . EMNLP, page 3622-3631. Association for Computational Linguistics, (2018)

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Detecting Hallucinated Content in Conditional Neural Sequence Generation., , , , , and . CoRR, (2020)f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation., , , , and . CoRR, (2022)Learning Controllable 3D Diffusion Models from Single-view Images., , , , , and . CoRR, (2023)Revisiting Self-Training for Neural Sequence Generation., , , and . CoRR, (2019)Intelligent Time-Adaptive Transient Stability Assessment System., , , , and . CoRR, (2016)Deep Learning Model to Estimate Air Pollution Using M-BP to Fill in Missing Proxy Urban Data., , , and . GLOBECOM, page 1-6. IEEE, (2017)Self-Supervised Representations Improve End-to-End Speech Translation., , , and . INTERSPEECH, page 1491-1495. ISCA, (2020)VizSeq: a visual analysis toolkit for text generation tasks., , , and . EMNLP/IJCNLP (3), page 253-258. Association for Computational Linguistics, (2019)Detection, Disambiguation, Re-ranking: Autoregressive Entity Linking as a Multi-Task Problem., , , , , and . ACL (Findings), page 1972-1983. Association for Computational Linguistics, (2022)Addressing Posterior Collapse with Mutual Information for Improved Variational Neural Machine Translation., , , and . ACL, page 8512-8525. Association for Computational Linguistics, (2020)