most citedFragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching

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cs.LG2026

scTrilemma: Balancing Identity, Invariance, and Fidelity in Single-Cell Representation Learning

Yunhak Oh, Yoonho Lee, Junseok Lee +9

Single-cell RNA-seq representation learning is fundamentally label-free: cell identities, states, and contexts are not fixed training targets, so what constitutes signal or nuisanc…

cs.LG2025★ 1 cited

FragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching

Joongwon Lee, Seonghwan Kim, Seokhyun Moon +2

We introduce FragFM, a novel hierarchical framework via fragment-level discrete flow matching for efficient molecular graph generation. FragFM generates molecules at the fragment l…