3 citations · 7 across the 28 of their papers we have counts for
4 papers · 1 filter
Dual Conditional Diffusion Models for Sequential Recommendation
Hongtao Huang, Chengkai Huang, Tong Yu +4
Recent advancements in diffusion models have shown promising results in sequential recommendation (SR). Existing approaches predominantly rely on implicit conditional diffusion mod…
Federated Large Language Models: Current Progress and Future Directions
Yuhang Yao, Jianyi Zhang, Junda Wu +11
Large Language Models have achieved impressive performance across diverse applications, yet their training typically depends on centralized data collection, raising serious privacy…
Embedding-Informed Adaptive Retrieval-Augmented Generation of Large Language Models
Chengkai Huang, Yu Xia, Rui Wang +4
Retrieval-augmented large language models (LLMs) have been remarkably competent in various NLP tasks. However, it was observed by previous works that retrieval is not always helpfu…
Foundation Models for Recommender Systems: A Survey and New Perspectives
Chengkai Huang, Tong Yu, Kaige Xie +3
Recently, Foundation Models (FMs), with their extensive knowledge bases and complex architectures, have offered unique opportunities within the realm of recommender systems (RSs).…