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Transformer Grammars: Augmenting Transformer Language Models with Syntactic Inductive Biases at Scale ...
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Diverse Pretrained Context Encodings Improve Document Translation ...
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Better {C}hinese Sentence Segmentation with Reinforcement Learning ...
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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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Unsupervised Bilingual POS Tagging with Markov Random Fields ...
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Unsupervised Bilingual POS Tagging with Markov Random Fields ...
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Knowledge-Rich Morphological Priors for Bayesian Language Models ...
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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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Ontology-Aware Token Embeddings for Prepositional Phrase Attachment ...
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Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning ...
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Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning ...
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