SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents
Table 1: Performance of various models on the entire Daily Mail test set using the limited length recall variants of Rouge with respect to the abstractive ground truth at 75 bytes. Entries with asterisk are statistically significant using 95% confidence interval with respect to the nearest model, as estimated by the Rouge script.
['[EMPTY]', 'Rouge-1', 'Rouge-2', 'Rouge-L']
While the abstractively trained SummaRuNNer performs on par with the state-of-the-art model, the extractively trained model significantly improves over their model.