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Ranking-Enhanced Unsupervised Sentence Representation Learning. (arXiv:2209.04333v1 [cs.CL])
cs.CL updates on arXiv.org arxiv.org
Previous unsupervised sentence embedding studies have focused on data
augmentation methods such as dropout masking and rule-based sentence
transformation methods. However, these approaches have a limitation of
controlling the fine-grained semantics of augmented views of a sentence. This
results in inadequate supervision signals for capturing a semantic similarity
of similar sentences. In this work, we found that using neighbor sentences
enables capturing a more accurate semantic similarity between similar
sentences. Based on this finding, we propose RankEncoder, which uses relations …
arxiv ranking representation representation learning unsupervised