arXiv:1712.09405cs.CL
Advances in Pre-Training Distributed Word Representations
Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.
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.
Nope, the paper says it's just using the FastText word embedding: https://nips2018creativity.github.io/doc/entendrepreneur.pdf which is just a particularly well-done word2vec: https://arxiv.org/pdf/1712.09405.pdf 'Lasker' and 'chess' no doubt co-occur quite strongly in their…
gwernView on HNParent context