  Text simplification lacks a universal standard of quality, and annotated
reference simplifications are scarce and costly. We propose to alleviate such
limitations by introducing REFeREE, a reference-free model-based metric with a
3-stage curriculum. REFeREE leverages an arbitrarily scalable pretraining stage
and can be applied to any quality standard as long as a small number of human
annotations are available. Our experiments show that our metric outperforms
existing reference-based metrics in predicting overall ratings and reaches
competitive and consistent performance in predicting specific ratings while
requiring no reference simplifications at inference time.
