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Zhonghui Wang

2 accepted papers

2025

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering

ACL 2025long

Extracting sentence embeddings from large language models (LLMs) is a practical direction, as it requires neither additional data nor fine-tuning. Previous studies usually focus on prompt engineering to guide LLMs to encode the core semantic information of the sentence into the embedding of the last…

2025

Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMs

ACL 2025long

Extracting sentence embeddings from large language models (LLMs) is a promising direction, as LLMs have demonstrated stronger semantic understanding capabilities. Previous studies typically focus on prompt engineering to elicit sentence embeddings from LLMs by prompting the model to encode sentence…

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