Beyond the Answers: Reviewing the Rationality of Multiple Choice Question Answering for the Evaluation of Large Language Models

In the field of natural language processing (NLP), Large Language Models (LLMs) have precipitated a paradigm shift, markedly enhancing performance in natural language generation tasks. Despite these advancements, the comprehensive evaluation of LLMs remains an inevitable challenge for the community. Recently, the utilization of Multiple Choice Question Answering (MCQA) as a benchmark for LLMs has gained considerable traction. This study investigates the rationality of MCQA as an evaluation method for LLMs. If LLMs genuinely understand the semantics of questions, their …

beyond challenge community cs.ai cs.cl evaluation language language generation language models language processing large language large language models llms multiple natural natural language natural language generation natural language processing nlp paradigm performance processing question question answering shift tasks