2 papers
cs.IR2026
Bi-NAS: Towards Effective and Personalized Explanation for Recommender Systems via Bi-Level Neural Architecture Search
Longfeng Wu, Yao Zhou, Tong Zeng +5
Recommender systems are vital in helping users navigate vast amounts of information, offering personalized suggestions and effective explanations for these recommendations. While p…
cs.IR2025
Collaborative Diffusion Model for Recommender System
Gyuseok Lee, Yaochen Zhu, Hwanjo Yu +2
Diffusion-based recommender systems (DR) have gained increasing attention for their advanced generative and denoising capabilities. However, existing DR face two central limitation…