SciCustom: A Framework for Custom Evaluation of Scientific Capabilities in Large Language Models
Researchers have developed SciCustom, a new framework designed to create custom benchmarks for evaluating the scientific capabilities of large language models. Existing benchmarks are often too generic or manually curated, failing to capture the specific skills needed for real-world scientific applications. SciCustom addresses this by organizing scientific knowledge into structured units, enabling the generation of tailored benchmarks from large datasets without requiring expert annotation or synthetic question generation. AI
IMPACT Enables more precise evaluation of LLMs in scientific domains, potentially leading to better-suited models for research.