What drives performance in molecular MPNNs? An operator-level factorial benchmark
This paper introduces an operator-level factorial benchmark that decomposes molecular MPNNs into distinct message-seed, fusion, and update components, revealing that message construction—particularly concatenation-based node-edge fusion—is the primary driver of performance, thereby providing targeted design heuristics that outperform monolithic architecture searches.