Connecting Molecules to AI Language Models
Enabling LLMs to understand molecular structures without fine-tuning
Graph2Token bridges the gap between molecular graphs and Large Language Models, allowing LLMs to process complex molecular structures by mapping graph data to language tokens.
- Creates an efficient alignment between graph structures and LLM token vocabulary
- Processes molecular data without requiring LLM backbone fine-tuning
- Constructs comprehensive molecule-text paired datasets from multiple biological sources
- Enhances LLM capabilities for molecular classification and regression tasks
Why it matters: This breakthrough enables powerful language models to analyze molecular structures for drug discovery, protein interaction modeling, and other critical biological applications—combining the generalization capabilities of LLMs with the specialized needs of molecular biology research.