Evaluating Language Models: A New Framework

This chapter explores the challenges of evaluating large language models (LLMs) in comparison to traditional human assessments like the SAT and MCAT. It highlights the limitations of current evaluation methods and the intricacies of understanding how LLMs function and make decisions. The discussion raises fundamental questions about the nature of intelligence and the relevance of human-designed tests for artificial systems.

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