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Keyword: word embeddings ×Clear all

2 claims from 1 paper

1. Computer Science › Topic Modeling

   Deep Contextualized Word Representations

   Peters, Neumann, Iyyer et al. · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · 2018

   The paper introduces word representations drawn from a pre-trained deep bidirectional language model, which vary with context and which the authors report improve existing systems on six language tasks.

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   1. Unchecked“We also present an analysis showing that exposing the deep internals of the pre-trained network is crucial, allowing downstream models to mix different types of semi-supervision signals.”
   2. UncheckedThe authors report that their new word representations slot easily into existing models and significantly improve the state of the art on six NLP tasks.“We show that these representations can be easily added to existing models and significantly improve the state of the art across six challenging NLP problems, including question answering, textual entailment and sentiment analysis.”