3 papers
cs.IR2026
L2Rec: Towards Dual-View Understanding of LLMs for Personalized Recommendation
Pingjun Pan, Tingting Zhou, Peiyao Lu +3
Adapting large language models (LLMs) for personalized recommendation requires aligning their general-purpose capabilities with user-specific preferences while effectively leveragi…
cs.AI2026
Hi-SAM: A Hierarchical Structure-Aware Multi-modal Framework for Large-Scale Recommendation
Pingjun Pan, Tingting Zhou, Peiyao Lu +3
Multi-modal recommendation has gained traction as items possess rich attributes like text and images. Semantic ID-based approaches effectively discretize this information into comp…
cs.IR2021
Zero Shot on the Cold-Start Problem: Model-Agnostic Interest Learning for Recommender Systems
Philip J. Feng, Pingjun Pan, Tingting Zhou +2
User behavior has been validated to be effective in revealing personalized preferences for commercial recommendations. However, few user-item interactions can be collected for new…