Qijie Shen — accepted AI-conference papers

2026

LLM Collaborative Filtering: User-Item Graph as New Language

Huachi Zhou, Yujing Zhang, Hao Chen, Qinggang Zhang, Qijie Shen, Feiran Huang +1

AAAI 2026technical

In collaborative filtering, learning effective embeddings for users and items from interaction data remains a central challenge. While recent efforts leverage large language models (LLMs) to enhance collaborative filtering, two critical limitations persist: (1) Efficiency: LLM-based inference is sig

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2024

Fine Tuning Out-of-Vocabulary Item Recommendation with User Sequence Imagination

Ruochen Liu, Hao Chen, Yuanchen Bei, Qijie Shen, Fangwei Zhong, Senzhang Wang +1

NeurIPS 2024spotlight

Recommending out-of-vocabulary (OOV) items is a challenging problem since the in-vocabulary (IV) items have well-trained behavioral embeddings but the OOV items only have content features. Current OOV recommendation models often generate 'makeshift' embeddings for OOV items from content features and…

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