A Diffusion Graph Transformer Model for Enhancing Top-k Recommendation Performance

The core message of this paper is to propose a novel Diffusion Graph Transformer (DiffGT) model that effectively denoises implicit user-item interactions in recommender systems by incorporating a directional diffusion process and a graph transformer architecture.