How to Balance Cost and Quality in AI Translation Evaluation – slator.com

As large language models (LLMs) gain prominence as state-of-the-art evaluators, prompt-based evaluation methods like GEMBA-MQM have emerged as powerful tools for assessing translation quality. However, LLM-based evaluation is expensive and computationally demanding, requiring vast amounts of tokens and incurring significant API call expenses. Scaling evaluation to large datasets quickly becomes impractical, raising a key question: […]