Enriching Word Vectors with Subword Information

TACL 2017 Piotr BojanowskiEdouard GraveArmand JoulinTomas Mikolov

Continuous word representations, trained on large unlabeled corpora are useful for many natural language processing tasks. Popular models that learn such representations ignore the morphology of words, by assigning a distinct vector to each word... (read more)

PDF Abstract

Evaluation Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help community compare results to other papers.