MORAD: Reinforcement Learning with Multi-Objective Rewards for RNA Inverse Design
cs.LG, q-bio.BM
Submitted: 2026-10-09
Updated: 2026-10-09
Comments: 18 pages, 5 figures. Jixin Tang and Ji Guo contributed equally. Project page: https://gabrile166.github.io/MORAD/
Code: https://github.com/COLA-Laboratory/RIDER
Project page: https://gabrile166.github.io/MORAD
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Training Diffusion Models with Reinforcement Learning
- Reinforcement learning on structure-conditioned categorical diffusion for protein inverse folding
- Denoising Diffusion Probabilistic Models
- RIDER: 3D RNA Inverse Design with Reinforcement Learning-Guided Diffusion
- Understanding the Effects of RLHF on LLM Generalisation and Diversity
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Structure-based RNA Design by Step-wise Optimization of Latent Diffusion Model
- RiboPO: Preference Optimization for Structure- and Stability-Aware RNA Design
- ProteinZero: Self-Improving Protein Generation via Online Reinforcement Learning
- Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
- DiffusionNFT: Online Diffusion Reinforcement with Forward Process
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks