An Interpretable and Scalable Framework for Evaluating Large Language Models

Xinhao Qu, Qiang Heng, Hao Zeng +1

Evaluation of large language models (LLMs) is increasingly critical, yet standard benchmarking methods rely on average accuracy, overlooking both the inherent stochasticity of LLM…