@inproceedings{rogers-etal-2017-many,
    title = "The (too Many) Problems of Analogical Reasoning with Word Vectors",
    author = "Rogers, Anna  and
      Drozd, Aleksandr  and
      Li, Bofang",
    editor = "Ide, Nancy  and
      Herbelot, Aur{\'e}lie  and
      M{\`a}rquez, Llu{\'i}s",
    booktitle = "Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*{SEM} 2017)",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/S17-1017/",
    doi = "10.18653/v1/S17-1017",
    pages = "135--148",
    abstract = "This paper explores the possibilities of analogical reasoning with vector space models. Given two pairs of words with the same relation (e.g. man:woman :: king:queen), it was proposed that the offset between one pair of the corresponding word vectors can be used to identify the unknown member of the other pair (king - man + woman = queen). We argue against such ``linguistic regularities'' as a model for linguistic relations in vector space models and as a benchmark, and we show that the vector offset (as well as two other, better-performing methods) suffers from dependence on vector similarity."
}