[2305.07824] A Simple and Plug-and-play Method for Unsupervised Sentence Representation Enhancement
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Computer Science > Computation and Language

arXiv:2305.07824 (cs)
[Submitted on 13 May 2023]

Title:A Simple and Plug-and-play Method for Unsupervised Sentence Representation Enhancement

Authors:Lingfeng Shen, Haiyun Jiang, Lemao Liu, Shuming Shi
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Abstract:Generating proper embedding of sentences through an unsupervised way is beneficial to semantic matching and retrieval problems in real-world scenarios. This paper presents Representation ALchemy (RepAL), an extremely simple post-processing method that enhances sentence representations. The basic idea in RepAL is to de-emphasize redundant information of sentence embedding generated by pre-trained models. Through comprehensive experiments, we show that RepAL is free of training and is a plug-and-play method that can be combined with most existing unsupervised sentence learning models. We also conducted in-depth analysis to understand RepAL.
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2305.07824 [cs.CL]
  (or arXiv:2305.07824v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2305.07824

Submission history

From: Lingfeng Shen [view email]
[v1] Sat, 13 May 2023 02:43:59 UTC (4,565 KB)
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