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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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Abstract:
This report documents the program and the outcomes of Dagstuhl Seminar 17042 "From Characters to Understanding Natural Language (C2NLU): Robust End-to-End Deep Learning for NLP". The seminar brought together researchers from different fields, including natural language processing, computational linguistics, deep learning and general machine learning. 31 participants from 22 academic and industrial institutions discussed advantages and challenges of using characters, i.e., "raw text", as input for deep learning models instead of language-specific tokens. Eight talks provided overviews of different topics, approaches and challenges in current natural language processing research. In five working groups, the participants discussed current natural language processing/understanding topics in the context of character-based modeling, namely, morphology, machine translation, representation learning, end-to-end systems and dialogue. In most of the discussions, the need for a more detailed model analysis was pointed ...
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Keyword:
Computer Science
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URL: https://dx.doi.org/10.4230/dagrep.7.1.129 http://drops.dagstuhl.de/opus/volltexte/2017/7248/
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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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