Diversity 5
- Can One Embedding Fit All? A Multi-Interest Learning Paradigm Towards Improving User Interest Diversity Fairness, (WWW'24)
- Enhancing Domain-Level and User-Level Adaptivity in Diversified Recommendation, (SIGIR'21)
- User-controllable Recommendation Against Filter Bubbles, (SIGIR'22)
- DGCN: Diversified Recommendation with Graph Convolutional Networks, (WWW'21)
- Controllable Multi-Interest Framework for Recommendation, (KDD'20)