Javen Qinfeng Shi

Boundary-region entanglement is a critical bottleneck for GNNs, and our adaptive approach boosts classification accuracy by over 3% while maintaining model stability.

Unseen single-cell perturbation effects can be predicted more accurately by explicitly modeling the latent, dynamic causal processes that drive cellular response.

LLMs can now explain chemical reactions from 4D molecular trajectories, thanks to a new benchmark and model designed to bridge the gap between dynamic molecular simulations and natural language understanding.