CSE443: Bioinformatics · 2024

BioAlign-QLoRA: Biomedical Knowledge Graph Alignment

Led a team research project developing a novel Knowledge Graph Separation methodology for quantifying structural alignment of LLM embeddings with biomedical knowledge graphs following QLoRA fine-tuning. Demonstrated 126% improvement in embedding geometric alignment with Phi-3 Mini.

[ KEY ]

Technical Highlights

  • 01

    Introduced a novel 'Knowledge Graph Separation' score quantifying geometric alignment between LLM embedding space and biological knowledge structures.

  • 02

    Achieved 83.8% accuracy with Mistral model, outperforming the pre-trained BioMistral-7B expert.

[ STK ]

Stack

PythonPyTorchQLoRALlama-3Mistral-7BKnowledge Graphs