AI RESEARCH

When Molecular Similarity Works: Property Cliffs Reveal Hidden Errors

arXiv CS.LG

ArXi:2605.17265v1 Announce Type: new Accurate prediction of molecular properties underpins drug discovery and material design, yet even state-of-the-art models remain vulnerable to localized failure modes that aggregate metrics cannot detect. The places where molecular similarity should be most helpful are also places where standard evaluation can be most misleading. Property cliffs expose this gap: structurally similar molecules can still differ sharply in target property, so models with competitive overall performance may fail in high-risk local neighborhoods.