2 citations · 2 across the 1 of their papers we have counts for
Showing cs.CLShow all
2 papers · 1 filter
cs.CL2019★ 2 cited
Better Word Embeddings by Disentangling Contextual n-Gram Information
Prakhar Gupta, Matteo Pagliardini, Martin Jaggi
Pre-trained word vectors are ubiquitous in Natural Language Processing applications. In this paper, we show how training word embeddings jointly with bigram and even trigram embedd…
cs.CL2018
Learning Word Vectors for 157 Languages
Edouard Grave, Piotr Bojanowski, Prakhar Gupta +2
Distributed word representations, or word vectors, have recently been applied to many tasks in natural language processing, leading to state-of-the-art performance. A key ingredien…