41 citations · 108 across the 26 of their papers we have counts for
4 papers · 1 filter
Efficient and Effective Adaptation of Multimodal Foundation Models in Sequential Recommendation
Junchen Fu, Xuri Ge, Xin Xin +5
Multimodal foundation models (MFMs) have revolutionized sequential recommender systems through advanced representation learning. While Parameter-efficient Fine-tuning (PEFT) is com…
Towards End-to-End Explainable Facial Action Unit Recognition via Vision-Language Joint Learning
Xuri Ge, Junchen Fu, Fuhai Chen +3
Facial action units (AUs), as defined in the Facial Action Coding System (FACS), have received significant research interest owing to their diverse range of applications in facial…
IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT
Junchen Fu, Xuri Ge, Xin Xin +4
Multimodal foundation models are transformative in sequential recommender systems, leveraging powerful representation learning capabilities. While Parameter-efficient Fine-tuning (…
An Empirical Study of Training ID-Agnostic Multi-modal Sequential Recommenders
Youhua Li, Hanwen Du, Yongxin Ni +4
Sequential Recommendation (SR) aims to predict future user-item interactions based on historical interactions. While many SR approaches concentrate on user IDs and item IDs, the hu…