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ScaleEval is an agent-debate-assisted framework for scalable meta-evaluation of LLMs used as evaluators, leveraging multiple communicative LLM agents to enable multi-round discussions. It lets users submit LLM outputs, evaluation criteria, and scenarios to conduct meta-evaluation and identify the best evaluator. It is distributed as a Python package (pip install scaleeval) with example criteria such as metaeval_creativity, metaeval_helpfulness, metaeval_interpretability, and metaeval_reasoning.
AI named ScalingEval in January 2026.