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Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Existing algorithms for aligning cross-lingual word vector spaces assume that vector spaces are approximately isomorphic. As a result, they perform poorly or fail completely on nonisomorphic spaces. Such non-isomorphism has been hypothesised to result from typological differences between languages. In this work, we ask whether non-isomorphism is also crucially a sign of degenerate word vector spaces. We present a series of experiments across diverse languages which show that variance indoi:10.18653/v1/2020.emnlp-main.257 fatcat:q6ah6muwnvblbhn6wmhtchifrm