Approximating Human Preferences Using a Multi-Judge Learned System

Eitán Sprejer, Fernando Avalos, Augusto Bernardi +3

Aligning LLM-based judges with human preferences is a significant challenge, as they are difficult to calibrate and often suffer from rubric sensitivity, bias, and instability. Ove…