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LLM as a judge explained

Benched.ai Editorial Team

Using large language models to evaluate other model outputs for scalable quality control and automated benchmarks

LLM-as-a-judge techniques use language models to score or compare outputs from other AI systems. Evaluation prompts describe desired qualities such as factual accuracy or helpfulness. The judge model then produces a rating or explanation. Enterprises apply this method to automate benchmark comparisons and continuous testing across chatbots and RAG pipelines.

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