An Information Minimization Based Contrastive Learning Model for Unsupervised Sentence Embeddings Learning

1 code implementation • COLING 2022 • Shaobin Chen, Jie zhou, Yuling Sun, Liang He

To address this problem, we present an information minimization based contrastive learning (InforMin-CL) model to retain the useful information and discard the redundant information by maximizing the mutual information and minimizing the information entropy between positive instances meanwhile for unsupervised sentence representation learning.

Contrastive Learning Semantic Textual Similarity +3