Towards making NLG a voice for interpretable Machine Learning
James Forrest, Somayajulu Gowri Sripada, Wei Pang, George M. Coghill · 2018
This paper presents a study to understand the issues related to using NLG to humanise explanations from a popular interpretable machine learning framework called LIME.Our study shows that selfreported rating of NLG explanation was higher than that for a non-NLG explanation.However, when tested for comprehension, the results were not as clearcut showing the need for performing more studies to uncover the factors responsible for high-quality NLG explanations.