36 citations · 65 across the 13 of their papers we have counts for
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cs.IR2025
Generative Representational Learning of Foundation Models for Recommendation
Zheli Zhou, Chenxu Zhu, Jianghao Lin +4
Developing a single foundation model with the capability to excel across diverse tasks has been a long-standing objective in the field of artificial intelligence. As the wave of ge…
cs.IR2025
LLM4Tag: Automatic Tagging System for Information Retrieval via Large Language Models
Ruiming Tang, Chenxu Zhu, Bo Chen +4
Tagging systems play an essential role in various information retrieval applications such as search engines and recommender systems. Recently, Large Language Models (LLMs) have bee…
cs.IR2025
Full-Stack Optimized Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation
Rong Shan, Jiachen Zhu, Jianghao Lin +5
In this paper, we address the lifelong sequential behavior incomprehension problem in large language models (LLMs) for recommendation, where LLMs struggle to extract useful informa…