MV-CLAM introduces a novel approach that enhances Large Language Models' ability to comprehend molecular structures by leveraging multiple complementary views of molecular data.

• Surpasses existing models by integrating multiple molecular representations rather than single-view approaches
• Employs cross-modal projection to create rich, contextual understanding of molecular structures
• Demonstrates superior performance in molecular interpretation tasks relevant to drug discovery and biomedical research
• Enables more human-like understanding of chemical and biomedical contexts

This advancement could accelerate pharmaceutical research by improving how AI systems interpret molecular structures, potentially leading to faster drug discovery processes and more accurate predictions of molecular interactions.

MV-CLAM: Multi-View Molecular Interpretation with Cross-Modal Projection via Language Model