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Factors Influencing the Surprising Instability of Word Embeddings

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arxiv 1804.09692 v1 pith:RLNT35XG submitted 2018-04-25 cs.CL

Laura Wendlandt , Jonathan K. Kummerfeld , Rada Mihalcea This is my paper · ORCID
classification cs.CL
keywords stabilitywordembeddingembeddingsfactorsanalyzeaspectbody
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Despite the recent popularity of word embedding methods, there is only a small body of work exploring the limitations of these representations. In this paper, we consider one aspect of embedding spaces, namely their stability. We show that even relatively high frequency words (100-200 occurrences) are often unstable. We provide empirical evidence for how various factors contribute to the stability of word embeddings, and we analyze the effects of stability on downstream tasks.

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  1. A framework for anomaly detection using language modeling, and its applications to finance

    cs.CL 2019-08 unverdicted novelty 4.0 of 10

    The paper offers a taxonomy connecting five types of textual anomaly in finance to signals from language model components, with examples and challenges.

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