Evaluating the Evaluators: Investigating LLM Judges for Personalized Writing Style Assessment

This paper was accepted at the Can We Trust AI Evaluation? Workshop at NeurIPS 2026.
We evaluate how good large language model (LLM) judges are for personalized writing tasks. This is important when a user’s preferred writing style is known (e.g., “upbeat”) and an LLM judge is used to evaluate whether generated text adheres to this preference. We examine how the writing task, the combination of generator and judge LLM, the evaluation objective, and general commonsense and reasoning ability impact LLM judge performance. To this end, we generate text with four LLMs for three long-form writing…