LLMs as Judges: A Comprehensive Survey on LLM-Based Evaluation Methods
Deep Papers
Evaluating Large Language Models
This chapter explores the methodologies used to assess the performance of large language models (LLMs) as evaluators. It covers various input evaluation types, such as item-wise and pair-wise assessments, and emphasizes the importance of benchmarks like linguistic quality and task-specific metrics. Furthermore, it discusses the role of human evaluators in enhancing evaluation accuracy and the applicability of LLMs in diverse contexts.
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