Efficient summarization with read-again and copy mechanism
Table 1: Different Read-Again Model. Ours denotes Read-Again models. C denotes copy mechanism. Ours-Opt-1 and Ours-Opt-2 are the models described in section 3.1.3. Size denotes the size of decoder vocabulary in a model.
['#Input', 'Model', 'Size', 'Rouge-1', 'Rouge-2', 'Rouge-L']
Results on Gigaword : We compare the performances of different architectures and report ROUGE scores in Tab. Our baselines include the ABS model of Rush et al. We allow the decoder to generate variable length summaries. As shown in Tab. We also observe that adding the copy mechanism further helps to improve performance: Even though the decoder vocabulary size of our approach with copy (15K) is much smaller than ABS (69K) and GRU (69K), it achieves a higher ROUGE score. Besides, our Multiple-Sentences model achieves the best performance.