69 citations · 84 across the 16 of their papers we have counts for
4 papers · 1 filter
DistilCSE: Effective Knowledge Distillation For Contrastive Sentence Embeddings
Chaochen Gao, Xing Wu, Peng Wang +4
Large-scale contrastive learning models can learn very informative sentence embeddings, but are hard to serve online due to the huge model size. Therefore, they often play the role…
TransAug: Translate as Augmentation for Sentence Embeddings
Jue Wang
While contrastive learning greatly advances the representation of sentence embeddings, it is still limited by the size of the existing sentence datasets. In this paper, we present…
ESimCSE: Enhanced Sample Building Method for Contrastive Learning of Unsupervised Sentence Embedding
Xing Wu, Chaochen Gao, Liangjun Zang +3
Contrastive learning has been attracting much attention for learning unsupervised sentence embeddings. The current state-of-the-art unsupervised method is the unsupervised SimCSE (…
Smoothed Contrastive Learning for Unsupervised Sentence Embedding
Xing Wu, Chaochen Gao, Yipeng Su +3
Contrastive learning has been gradually applied to learn high-quality unsupervised sentence embedding. Among the previous un-supervised methods, the latest state-of-the-art method,…