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Evaluating Trustworthiness in Language Models
This chapter explores a recent research paper assessing trustworthiness in language models, focusing on eight evaluation perspectives like toxicity and fairness. It discusses the development of scalable methods and a GitHub toolbox for model assessment, while addressing the balance between ethical guidelines and instruction-following behavior. The chapter also highlights ongoing challenges in benchmarking these models and the implications for trust and performance evaluation in AI.