3 papers
cs.CV2025
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…
cs.CE2025
Chem-R: Learning to Reason as a Chemist
Weida Wang, Benteng Chen, Di Zhang +14
Although large language models (LLMs) have significant potential to advance chemical discovery, current LLMs lack core chemical knowledge, produce unreliable reasoning trajectories…
cs.AI2025
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…