Summary
Evaluating large language models (LLMs) is a critical process in the field of artificial intelligence, as these models are central to a wide array of applications, from natural language processing to automated decision-making systems.
By assessing their performance, interpretability, and ethical implications, we gain insights into their strengths and limitations, enabling more effective deployment in real-world scenarios.
This evaluation looks at traditional metrics like accuracy and efficiency, as well as broader aspects like fairness, bias, and generalization. Evaluating LLMs ensures that LLMs are reliable, transparent, and aligned with human values.