NLG Evaluation: Past, Present, Future
A new paper on arXiv reviews the evolution of Natural Language Generation (NLG) evaluation methods. It traces the shift from early linguistic ties to the current machine learning-centric approach, highlighting the emergence of techniques like LLM-as-Judge. The paper anticipates a future where impact, qualitative aspects, and safety evaluations will gain prominence as NLG technology becomes more widespread. AI
IMPACT Highlights the increasing importance of safety and qualitative evaluation as NLG technology becomes more integrated into daily life.