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Transformer Grammars: Augmenting Transformer Language Models with Syntactic Inductive Biases at Scale ...
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A Generative Framework for Simultaneous Machine Translation ...
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Pretraining the Noisy Channel Model for Task-Oriented Dialogue ...
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Counterfactual Data Augmentation for Neural Machine Translation ...
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Better Document-Level Machine Translation with Bayes’ Rule
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In: Transactions of the Association for Computational Linguistics, Vol 8, Pp 346-360 (2020) (2020)
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Learning to Discover, Ground and Use Words with Segmental Neural Language Models ...
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From Characters to Understanding Natural Language (C2NLU): Robust End-to-End Deep Learning for NLP (Dagstuhl Seminar 17042)
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Learning to Create and Reuse Words in Open-Vocabulary Neural Language Modeling ...
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From Characters to Understanding Natural Language (C2NLU): Robust End-to-End Deep Learning for NLP (Dagstuhl Seminar 17042) ...
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Learning to Compose Words into Sentences with Reinforcement Learning ...
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Learning Bilingual Word Representations by Marginalizing Alignments ...
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