most citedA Strong Baseline for Learning Cross-Lingual Word Embeddings from Sentence Alignments

2 citations · 4 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CL2019★ 2 cited

Training on Synthetic Noise Improves Robustness to Natural Noise in Machine Translation

Vladimir Karpukhin, Omer Levy, Jacob Eisenstein +1

We consider the problem of making machine translation more robust to character-level variation at the source side, such as typos. Existing methods achieve greater coverage by apply…

cs.CL2016★ 2 cited

A Strong Baseline for Learning Cross-Lingual Word Embeddings from Sentence Alignments

Omer Levy, Anders Søgaard, Yoav Goldberg

While cross-lingual word embeddings have been studied extensively in recent years, the qualitative differences between the different algorithms remain vague. We observe that whethe…