FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language Models

arXiv:2404.06003v1 Announce Type: new
Abstract: The rapid development of large language model (LLM) evaluation methodologies and datasets has led to a profound challenge: integrating state-of-the-art evaluation techniques cost-effectively while ensuring reliability, reproducibility, and efficiency. Currently, there is a notable absence of a unified and adaptable framework that seamlessly integrates various evaluation approaches. Moreover, the reliability of evaluation findings is often questionable due to potential data contamination, with the evaluation efficiency commonly overlooked when facing the substantial costs associated with LLM …

abstract art arxiv challenge cost cs.ai cs.cl datasets development efficiency evaluation framework language language model language models large language large language model large language models llm modular reliability reproducibility state trustworthy type