A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising
Table 3: Results on the English Gigaword dataset. Numbers are collected from original papers. The best performance is in bold.
['Model', 'R1', 'R2', 'RL']
For the English Gigaword sentence compression dataset, the input text is the first sentence of a news article, and the reference summary is the article’s headline. The size of train/val/test is 3.8M/189k/1,937 respectively, after filtering out data examples with articles containing only ”UNK” tokens. TED outperforms all the unsupervised baselines.