A dual-graph transformer leads all molecular prediction benchmarks.

The model captures atoms, bonds, and stereochemistry simultaneously, outperforming prior architectures that each handled only one encoding type.

Drug-discovery and materials science adoption remains untested outside the benchmark datasets.

Sources: Nature