A Generative Approach to Titling and Clustering Wikipedia Sections
Table 5: Results on Gigaword heading generation. The correlations between extractive score and model performance are stronger than for the Wikipedia corpus for all models. All correlations are statistically significant.
['[EMPTY]', 'Rouge-1', 'R.-L', 'P. Corr']
et al. Like Trans, the MASS model from Song et al. From our models, the transformer decoder performs the best overall. However, the attention-based decoders Trans and Rnn+Attn also have the highest partial correlations, suggesting much of their performance stems from extractive titles. For all models the partial correlations between Rouge-L and extractive score are higher for the Gigaword corpus than for the Wikipedia corpus.