Where Should Physics Enter a Molecular Crystal Generator?

arXiv:2609.36398 · q-bio.BM, cs.AI, cs.CE · Submitted 2026-09-28 · Read on arXiv

q-bio.BM, cs.AI, cs.CE

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/HaCTang/CrystAF

Terminology

• Calibration — 13× in this paper · explained in 7 episodes
• GRPO — 11× in this paper · explained in 6 episodes
• Distillation — 10× in this paper · explained in 2 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Reinforcement Learning — 7× in this paper · explained in 4 episodes
• Alignment — 6× in this paper · explained in 1 episode
• Diffusion Model — 4× in this paper · explained in 8 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Flow Matching — 4× in this paper · explained in 8 episodes
• Generative Model — 4× in this paper · explained in 2 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• In International Conference on Learning Representations — 3× in this paper
• Cambridge Structural Database — 2× in this paper
• Diffusion Models — 2× in this paper · explained in 6 episodes
• AUC — 1× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Flow Matching Model — 1× in this paper · explained in 2 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Inverse Problem — 1× in this paper · explained in 2 episodes
• Physical Constraints — 1× in this paper · explained in 7 episodes
• Scaling Laws — 1× in this paper · explained in 4 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Mean Flows for One-step Generative Modeling
• AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation
• MeanFlowNFT: Bringing Forward-Process RL to Average-Velocity Generators
• Flow-GRPO: Training Flow Matching Models via Online RL
• Fast Organic Crystal Structure Prediction with Unit Cell Flow Matching
• PackFlow: Generative Molecular Crystal Structure Prediction via Reinforcement Learning Alignment
• UMA: A Family of Universal Models for Atoms
• MolCrystalFlow: Molecular Crystal Structure Prediction via Flow Matching
• DiffusionNFT: Online Diffusion Reinforcement with Forward Process

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