4 papers
FedAFD: Multimodal Federated Learning via Adversarial Fusion and Distillation
Min Tan, Junchao Ma, Yinfu Feng +6
Multimodal Federated Learning (MFL) enables clients with heterogeneous data modalities to collaboratively train models without sharing raw data, offering a privacy-preserving frame…
LLM-I2I: Boost Your Small Item2Item Recommendation Model with Large Language Model
Yinfu Feng, Yanjing Wu, Rong Xiao +1
Item-to-Item (I2I) recommendation models are widely used in real-world systems due to their scalability, real-time capabilities, and high recommendation quality. Research to enhanc…
ENCODE: Breaking the Trade-Off Between Performance and Efficiency in Long-Term User Behavior Modeling
Wenji Zhou, Yuhang Zheng, Yinfu Feng +5
Long-term user behavior sequences are a goldmine for businesses to explore users' interests to improve Click-Through Rate. However, it is very challenging to accurately capture use…
Hi-Gen: Generative Retrieval For Large-Scale Personalized E-commerce Search
Yanjing Wu, Yinfu Feng, Jian Wang +4
Leveraging generative retrieval (GR) techniques to enhance search systems is an emerging methodology that has shown promising results in recent years. In GR, a text-to-text model m…