3 papers
cs.IR2025
Tokenize Once, Recommend Anywhere: Unified Item Tokenization for Multi-domain LLM-based Recommendation
Yu Hou, Won-Yong Shin
Large language model (LLM)-based recommender systems have achieved high-quality performance by bridging the discrepancy between the item space and the language space through item t…
cs.IR2025
Fine-Tuning Diffusion-Based Recommender Systems via Reinforcement Learning with Reward Function Optimization
Yu Hou, Hua Li, Ha Young Kim +1
Diffusion models recently emerged as a powerful paradigm for recommender systems, offering state-of-the-art performance by modeling the generative process of user-item interactions…
cs.IR2024
Collaborative Filtering Based on Diffusion Models: Unveiling the Potential of High-Order Connectivity
Yu Hou, Jin-Duk Park, Won-Yong Shin
A recent study has shown that diffusion models are well-suited for modeling the generative process of user-item interactions in recommender systems due to their denoising nature. H…