RNA Design via Conditioned Flow Matching and Finite-Policy Reinforcement Learning

arXiv:2609.36885 · q-bio.BM, cs.LG · Submitted 2026-09-29 · Read on arXiv

q-bio.BM, cs.LG

Submitted: 2026-09-29

Updated: 2026-09-29

Code: https://github.com/John-Lin98/RNA-IFlow

Terminology

• Flow Matching — 18× in this paper · explained in 8 episodes
• Benchmark — 12× in this paper · explained in 2 episodes
• Regularization — 6× in this paper · explained in 3 episodes
• Reinforcement Learning — 6× in this paper · explained in 4 episodes
• Two-Stage Framework — 5× in this paper · explained in 2 episodes
• Structural Constraints — 4× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Flow-to-Policy Mapping — 3× in this paper
• Robustness — 3× in this paper · explained in 5 episodes
• Structure-Preserving Policy Dynamics — 3× in this paper
• Thermodynamic Trajectory Refinement — 3× in this paper
• Actor — 2× in this paper · explained in 3 episodes
• Benchmarking — 2× in this paper · explained in 4 episodes
• Decode — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Reinforcement Learning (RL) — 2× in this paper · explained in 25 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Action Space — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Computational Biology — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Distribution Shift — 1× in this paper · explained in 6 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 5 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Two-stage training — 1× in this paper · explained in 2 episodes

Sources

• Designing RNAs with Language Models
• GoForth: Language Models for RNA Design under Structure, Sequence, and Coding Constraints
• Proximal Policy Optimization Algorithms
• Fast and Versatile RNA Design via Motif-level Divide-and-Conquer and Structure-level Rival Search

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