LLMs as Judges: A Comprehensive Survey on LLM-Based Evaluation Methods
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Enhancing Large Language Models: Evaluation and Improvement Techniques
This chapter explores various evaluation methods for large language models, emphasizing the use of specific datasets to aggregate performance insights. Techniques such as reward modeling, data annotation, and leveraging synthetic data are discussed to improve model accuracy and mitigate biases.
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