collaborators

5 papers

cs.CE2026

LineageFlow: Flow Matching for High-Fidelity Family-Aware Protein Sequence Generation

Langzhang Liang, Ming Yang, Yi Feng +6

Protein sequence generation for engineering requires samples that are biophysically plausible and, when targeting a family/domain, remain recognizable members while exploring withi…

physics.chem-ph2026

UniField: RBF-Guided Electron Density Fusion for Enhanced Molecular Representations

Wei Zhang, Kun Li, Jiameng Chen +4

Current 3D geometric molecular representations predominantly focus on discrete atomic skeletons, inherently overlooking the continuous electron density (ED) field that fundamentall…

cs.LG2026

When Molecular Similarity Works: Property Cliffs Reveal Hidden Errors

Di Hu, Kun Li, Haojie Rao +6

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 aggrega…

cs.LG2026

Rethinking Molecular OOD Generalization via Target-Aware Source Selection

Zhuohao Lin, Kun Li, Jiameng Chen +4

Robust prediction of molecular properties under extreme out-of-distribution (OOD) scenarios is a pivotal bottleneck in AI-driven drug discovery. Current scaffold-splitting protocol…

cs.AI2026

From Single-Step Edit Response to Multi-Step Molecular Optimization

Haojie Rao, Kun Li, Yida Xiong +5

Conditional molecular optimization aims to edit a molecule to realize a specified property shift. In practice, structurally similar molecule data is scarce, while decisions are inh…