No Free Labels: Limitations of LLM-as-a-Judge Without Human Grounding

Understand

Reliable evaluation of large language models (LLMs) is critical as their deployment rapidly expands, particularly in high-stakes domains such as business and finance.

• The LLM-as-a-Judge framework, which uses prompted LLMs to evaluate response quality, is appealing due to its scalability, low cost, and strong correlations with human stylistic preferences.
• However, it remains unclear how accurately these methods can assess response quality in domains where correctness matters more than style.
• To address this gap, we introduce the Business and Finance Fundamentals Benchmark (BFF-Bench), a dataset of 160 challenging questions and long-form responses authored by financial professionals.