AAAI:SAP 2020 - Jiang et al.
Incremental Sense Weight Training for In-Depth Interpretation of Contextualized Word Embeddings
Xinyi Jiang, Zhengzhe Yang, Jinho D. Choi
Abstract
We present a novel online algorithm that learns the essence of each dimension in word embeddings. We first mask dimensions determined unessential by our algorithm, apply the masked word embeddings to a word sense disambiguation task (WSD), and compare its performance against the one achieved by the original embeddings. Our results show that the masked word embeddings do not hurt the performance and can improve it by 3%.
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