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cs.IR2025
LLM-based Bi-level Multi-interest Learning Framework for Sequential Recommendation
Shutong Qiao, Chen Gao, Wei Yuan +2
Sequential recommendation (SR) leverages users' dynamic preferences, with recent advances incorporating multi-interest learning to model diverse user interests. However, most multi…
cs.IR2025
Multi-view Intent Learning and Alignment with Large Language Models for Session-based Recommendation
Shutong Qiao, Wei Zhou, Junhao Wen +4
Session-based recommendation (SBR) methods often rely on user behavior data, which can struggle with the sparsity of session data, limiting performance. Researchers have identified…
cs.IR2025
Simulating Filter Bubble on Short-video Recommender System with Large Language Model Agents
Nicholas Sukiennik, Haoyu Wang, Zailin Zeng +2
An increasing reliance on recommender systems has led to concerns about the creation of filter bubbles on social media, especially on short video platforms like TikTok. However, th…