Online and Linear-Time Attention by Enforcing Monotonic Alignments
Table 3: ROUGE F-measure scores for sentence summarization on the Gigaword test set of rush2015neural. rush2015neural reports ROUGE recall scores, so we report the F-1 scores computed for that approach from chopra2016abstractive. As is standard, we report unigram, bigram, and longest common subsequence metrics as R-1, R-2, and R-L respectively.
['Method', 'R-1', 'R-2', 'R-L']
While the monotonic alignment model outperformed existing models by a substantial margin, it fell slightly behind the model of \citemainliu2016text which we used as a baseline. The higher performance of our model and the model of \citemainliu2016text can be partially explained by the fact that their encoders have roughly twice as many layers as most models proposed in the literature.