BlendCSE: blend contrastive learnings for sentence embeddings with rich semantics and transferability

BlendCSE: blend contrastive learnings for sentence embeddings with rich semantics and transferability

Sentence representation is one of the most fundamental research topics in natural language processing (NLP), as its quality directly affects various downstream task performances. Recent studies for sentence representations have established state-of-the-art (SOTA) performance on semantic representati...

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書目詳細資料
Main Authors:	Xu, Jiahao, Soh, Charlie Zhanyi, Xu, Liwen, Chen, Lihui
其他作者:	School of Electrical and Electronic Engineering
格式:	Article
語言:	English
出版:	2024
主題:	Engineering::Electrical and electronic engineering Semantic Sentence Embedding Contrastive Learning
在線閱讀:	https://hdl.handle.net/10356/173052
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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