Abstractive Summarization Improved by WordNet-based Extractive Sentences
Table 2: ROUGE F1 scores on CNN/Daily Mail non-anonymized testing dataset for all the controlled experiment models mentioned above. According to the official ROUGE usage description, all our ROUGE scores have a 95% confidence interval of at most ±0.25. PGN, Cov, ML, RL are abbreviations for pointer-generator, coverage, mixed-objective learning and reinforcement learning. Models with subscript a were trained and tested on the anonymized CNN/Daily Mail dataset, as well as with ∗ are the state-of-the-art extractive and abstractive summarization models on the anonymized dataset by now.
['Models', 'ROUGE  [BOLD] F1 scores 1', 'ROUGE  [BOLD] F1 scores 2', 'ROUGE  [BOLD] F1 scores L']
It counts the number of overlapping basic units including n-grams, longest common subsequences (LCS). We carry out the experiments based on original dataset, i.e., non-anonymized version of data. Attn + PGN, which is 0.09 points lower than the former result.