One Sequence, Many Decodings: CAGenMol-2 Recasts Drug Design as Masked Molecular Inference
cs.LG, cs.AI
Submitted: 2026-09-28
Updated: 2026-09-28
Code: https://github.com/Lee612-1/CAGenMol-2
Sources
- ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction
- Deep Ensembles: A Loss Landscape Perspective
- xVal: A Continuous Numerical Tokenization for Scientific Language Models
- 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction
- GenMol: A Drug Discovery Generalist with Discrete Diffusion
- Generating 3D Molecules for Target Protein Binding
- Proximal Policy Optimization Algorithms
- Efficient Evolutionary Search Over Chemical Space with Large Language Models
- LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning
- LlaSMol: Advancing Large Language Models for Chemistry with a Large-Scale, Comprehensive, High-Quality Instruction Tuning Dataset
- MolChord: Structure-Sequence Alignment for Protein-Guided Drug Design
- FoNE: Precise Single-Token Number Embeddings via Fourier Features
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