Rubric-based Evaluation

An evaluation method in which human reviewers assess the quality of AI system outputs against defined criteria such as correctness, relevance, helpfulness, safety, or fluency, providing judgments that complement or validate automated evaluation metrics.

An evaluation method that uses software, benchmarks, metrics, or models to assess the quality, correctness, or performance of AI systems without manual review.

An evaluation approach that uses another trained model to assess the quality, correctness, safety, or other properties of an AI system's outputs.

An evaluation method that uses a large language model to assess the quality, correctness, or other attributes of AI-generated outputs.

An evaluation method that assigns an independent score to each individual model response using defined criteria, without comparing it directly to another response.

An evaluation method in which subject matter experts assess the quality, accuracy, safety, or effectiveness of an AI system, model, or output using their domain knowledge and established criteria.