Papers by Shulan Ruan

1 papers
Refining Sentence Embedding Model through Ranking Sentences Generation with Large Language Models (2025.findings-acl)

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Challenge: Sentence embedding is essential for many NLP tasks, but reliance on manual labels limits scalability.
Approach: They propose a method for controlling the generation direction of large language models in the latent space by integrating ranking information and semantic information.
Outcome: The proposed method achieves new SOTA performance with a modest cost in ranking sentence synthesis.

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