Global Encoding for Abstractive Summarization
Table 2: F-Score of ROUGE on LCSTS.
['[BOLD] Model', '[BOLD] R-1', '[BOLD] R-2', '[BOLD] R-L']
In the experiments on the two datasets, our model achieves advantages of ROUGE score over the baselines, and the advantages of ROUGE score on the LCSTS are significant. We compare the F1 scores of our model with those of the baseline models (reported in their original articles) and our own implementation of the attention-based seq2seq. Compared with the conventional seq2seq model, our model owns an advantage of ROUGE-2 score 3.7 and 1.5 on the LCSTS and Gigaword respectively.