An Empirical Study on Post-processing Methods for Word Embeddings

ICLR 2020 Shuai TangMahta MousaviVirginia R. de Sa

Word embeddings learnt from large corpora have been adopted in various applications in natural language processing and served as the general input representations to learning systems. Recently, a series of post-processing methods have been proposed to boost the performance of word embeddings on similarity comparison and analogy retrieval tasks, and some have been adapted to compose sentence representations... (read more)

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