Comparative Analysis of LLaMA and ChatGPT Embeddings for Molecule Embedding

Purpose: Large Language Models (LLMs) like ChatGPT and LLaMA are increasingly recognized for their potential in the field of cheminformatics, particularly in interpreting Simplified Molecular Input Line Entry System (SMILES), a standard method for representing chemical structures. These LLMs can decode SMILES strings into vector representations, providing a novel approach to understanding chemical graphs.
Methods: We investigate the performance of ChatGPT and LLaMA in embedding SMILES strings. Our evaluation focuses on two key applications: molecular property (MP) prediction and drug-drug …

analysis chatgpt comparative analysis cs.ai cs.cl cs.lg decode embedding embeddings language language models large language large language models line llama llms novel q-bio.bm simplified standard strings vector