一作SIGIR 2026Oral· Information Retrieval (Full)
Fusion and Alignment Enhancement with Large Language Models for Tail-item Sequential Recommendation
Zhifu Wei · Yizhou Dang · Guibing Guo · Chuang Zhao · Zhu Sun
摘要
Sequential Recommendation (SR) learns user preferences from their historical interaction sequences and provides personalized suggestions. In real-world scenarios, most items exhibit sparse interactions, known as the tail-item problem. This issue limits the model's ability to accurately capture it...