Beyond LLM-as-a-Judge: Deterministic Metrics for Multilingual Generative Text Evaluation

ArXi:2604.05083v1 Announce Type: cross While Large Language Models (LLMs) are increasingly adopted as automated judges for evaluating generated text, their outputs are often costly, and highly sensitive to prompt design, language, and aggregation strategies, severely, which limits reproducibility. To address these challenges, we propose \textbf{\textit{OmniScore}}, a family of complementary, deterministic learned metrics developed using small size ($<$1B) parameter models.