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cs.CL2025
Refining Sentence Embedding Model through Ranking Sentences Generation with Large Language Models
Liyang He, Chenglong Liu, Rui Li +4
Sentence embedding is essential for many NLP tasks, with contrastive learning methods achieving strong performance using annotated datasets like NLI. Yet, the reliance on manual la…
cs.CL2023
Description-Enhanced Label Embedding Contrastive Learning for Text Classification
Kun Zhang, Le Wu, Guangyi Lv +6
Text Classification is one of the fundamental tasks in natural language processing, which requires an agent to determine the most appropriate category for input sentences. Recently…
cs.CL2020
R-Net: Relation of Relation Learning Network for Sentence Semantic Matching
Kun Zhang, Le Wu, Guangyi Lv +3
Sentence semantic matching is one of the fundamental tasks in natural language processing, which requires an agent to determine the semantic relation among input sentences. Recentl…