A personalized calibration network that combines LLM answers to multiple rubric questions predicted human judges' overall satisfaction scores on dialogues about twice as accurately as the uncalibrated LLM.
In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Process- ing, pages 10967–10982, Singapore
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LLM-Rubric: A Multidimensional, Calibrated Approach to Automated Evaluation of Natural Language Texts
A personalized calibration network that combines LLM answers to multiple rubric questions predicted human judges' overall satisfaction scores on dialogues about twice as accurately as the uncalibrated LLM.