From Guidelines to Guarantees: A Graph-Based Evaluation Harness for Domain-Specific Evaluation of LLMs

1. 1Transform structured clinical guidelines into a queryable knowledge graph
2. 2Instantiate evaluation queries via graph traversal
3. 3Evaluate LLM performance using the dynamically generated queries
4. 4Refine the evaluation framework based on the results

AI engineers and researchers benefit from this approach as it provides a comprehensive and maintainable evaluation framework for domain-specific LLMs, enabling them to assess model performance more accurately

💡 Graph-based evaluation can provide comprehensive and contamination-resistant benchmarks for domain-specific LLMs

📈 Graph-based evaluation harness for LLMs provides guarantees for domain-specific evaluation