3 papers
cs.CL2026
LLM-based Embeddings: Attention Values Encode Sentence Semantics Better Than Hidden States
Yeqin Zhang, Yunfei Wang, Jiaxuan Chen +3
Sentence representations are foundational to many Natural Language Processing (NLP) applications. While recent methods leverage Large Language Models (LLMs) to derive sentence repr…
cs.CL2025
Learning to Compress: Unlocking the Potential of Large Language Models for Text Representation
Yeqin Zhang, Yizheng Zhao, Chen Hu +4
Text representation plays a critical role in tasks like clustering, retrieval, and other downstream applications. With the emergence of large language models (LLMs), there is incre…
cs.CL2025
Retrospex: Language Agent Meets Offline Reinforcement Learning Critic
Yufei Xiang, Yiqun Shen, Yeqin Zhang +1
Large Language Models (LLMs) possess extensive knowledge and commonsense reasoning capabilities, making them valuable for creating powerful agents. However, existing LLM agent fram…