Expert Tax Judge

Research on "expert tax judge" (or more broadly, LLMs as judges) focuses on developing and evaluating large language models (LLMs) capable of reliably assessing the quality of other LLMs' outputs, a crucial task given the rapid advancement of these models. Current research emphasizes mitigating biases (e.g., position bias, various social biases) within these "judge" LLMs, exploring diverse model architectures (including ensembles of smaller models) to improve accuracy and reduce costs, and developing robust evaluation metrics beyond simple agreement. This work is significant for advancing the trustworthiness and reliability of LLM evaluations, ultimately improving the development and deployment of LLMs across various applications.