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    <abstract>We introduce a new approach for smoothing and improving the quality of word embeddings. We consider a method of fusing word embeddings that were trained on the same corpus but with different initializations. We project all the models to a shared vector space using an efficient implementation of the Generalized Procrustes Analysis (GPA) procedure, previously used in multilingual word translation. Our word representation demonstrates consistent improvements over the raw models as well as their simplistic average, on a range of tasks. As the new representations are more stable and reliable, there is a noticeable improvement in rare word evaluations.</abstract>
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%0 Conference Proceedings
%T Denoising Word Embeddings by Averaging in a Shared Space
%A Caciularu, Avi
%A Dagan, Ido
%A Goldberger, Jacob
%Y Ku, Lun-Wei
%Y Nastase, Vivi
%Y Vulić, Ivan
%S Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F caciularu-etal-2021-denoising
%X We introduce a new approach for smoothing and improving the quality of word embeddings. We consider a method of fusing word embeddings that were trained on the same corpus but with different initializations. We project all the models to a shared vector space using an efficient implementation of the Generalized Procrustes Analysis (GPA) procedure, previously used in multilingual word translation. Our word representation demonstrates consistent improvements over the raw models as well as their simplistic average, on a range of tasks. As the new representations are more stable and reliable, there is a noticeable improvement in rare word evaluations.
%R 10.18653/v1/2021.starsem-1.28
%U https://aclanthology.org/2021.starsem-1.28
%U https://doi.org/10.18653/v1/2021.starsem-1.28
%P 294-301

Markdown (Informal)

[Denoising Word Embeddings by Averaging in a Shared Space](https://aclanthology.org/2021.starsem-1.28) (Caciularu et al., *SEM 2021)

• Denoising Word Embeddings by Averaging in a Shared Space (Caciularu et al., *SEM 2021)

ACL

• Avi Caciularu, Ido Dagan, and Jacob Goldberger. 2021. Denoising Word Embeddings by Averaging in a Shared Space. In Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics, pages 294–301, Online. Association for Computational Linguistics.