Evaluating bilingual word embeddings on the long tail
Fabienne Braune, Tobias Eder, Viktor Hangya, Alexander Fraser
NAACL 2018

Bilingual word embeddings are useful for bilingual lexicon induction,
the task of mining translations of given words. Many studies have
shown that bilingual word embeddings perform well for bilingual
lexicon induction but they focused on frequent words in general
domains. For many applications, bilingual lexicon induction of rare
and domain-specific words is of critical importance. Therefore, we
design a new task to evaluate bilingual word embeddings on rare
words in different domains. We show that state-of-the-art approaches
fail on this task and present simple new techniques to improve
bilingual word embeddings for mining rare words. We release new gold
standard datasets and code to stimulate research on this task.