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Paper Information

lrec2018-main-008

Advances in Pre-Training Distributed Word Representations

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Title

Advances in Pre-Training Distributed Word Representations

Abstract

Many Natural Language Processing applications nowadays rely on pre-trained word representations estimated from large text corpora such as news collections, Wikipedia and Web Crawl. In this paper, we show how to train high-quality word vector representations by using a combination of known tricks that are however rarely used together. The main result of our work is the new set of publicly available pre-trained models that outperform the current state of the art by a large margin on a number of tasks.


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