4 papers
The Underappreciated Power of Vision Models for Graph Structural Understanding
Xinjian Zhao, Wei Pang, Zhongkai Xue +6
Graph Neural Networks operate through bottom-up message-passing, fundamentally differing from human visual perception, which intuitively captures global structures first. We invest…
Embedding in Recommender Systems: A Survey
Maolin Wang, Xinjian Zhao, Wanyu Wang +9
Recommender systems have become an essential component of many online platforms, providing personalized recommendations to users. A crucial aspect is embedding techniques that conv…
AOT*: Efficient Synthesis Planning via LLM-Empowered AND-OR Tree Search
Xiaozhuang Song, Xuanhao Pan, Xinjian Zhao +4
Retrosynthesis planning enables the discovery of viable synthetic routes for target molecules, playing a crucial role in domains like drug discovery and materials design. Multi-ste…
Rethinking Spectral Augmentation for Contrast-based Graph Self-Supervised Learning
Xiangru Jian, Xinjian Zhao, Wei Pang +4
The recent surge in contrast-based graph self-supervised learning has prominently featured an intensified exploration of spectral cues. Spectral augmentation, which involves modify…