3 papers
cs.CL2025
QZhou-Embedding Technical Report
Peng Yu, En Xu, Bin Chen +2
We present QZhou-Embedding, a general-purpose contextual text embedding model with exceptional text representation capabilities. Built upon the Qwen2.5-7B-Instruct foundation model…
cs.IR2025
Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval
Luo Ji, Feixiang Guo, Teng Chen +9
Despite the recent advancement in Retrieval-Augmented Generation (RAG) systems, most retrieval methodologies are often developed for factual retrieval, which assumes query and posi…
cs.IR2024
Towards a Unified Paradigm: Integrating Recommendation Systems as a New Language in Large Models
Kai Zheng, Qingfeng Sun, Can Xu +2
This paper explores the use of Large Language Models (LLMs) for sequential recommendation, which predicts users' future interactions based on their past behavior. We introduce a ne…