Associate Professor, Dalian University of Technology
2 papers at NeurIPS 2025
We propose UniteFormer, a unified neural solver that supports node-only, edge-only, and hybrid input types through a single model trained via joint edge-node modalities.
We propose MTRec, a novel sequential recommendation framework which uses a learned mental reward model to guide the recommendation model to align with users' real preferences.
