The major improvements come from contextualized BERT embeddings rather than word2vec and ELMo, and from fine-tuning BERT on large NLI datasets.
our goal in this paper is to devise an automated evaluation metric assigning a single holistic score to any system-generated text by comparing it against human references for content matching.