Papers › An Editorial Network for Enhanced Document Summarization

An Editorial Network for Enhanced Document Summarization

27 Feb 2019WS 2019 11arXiv:1902.10360archive 2025-07-28

Edward Moroshko, Guy Feigenblat, Haggai Roitman, David Konopnicki

We suggest a new idea of Editorial Network - a mixed extractive-abstractive summarization approach, which is applied as a post-processing step over a given sequence of extracted sentences. Our network tries to imitate the decision process of a human editor during summarization. Within such a process, each extracted sentence may be either kept untouched, rephrased or completely rejected. We further suggest an effective way for training the "editor" based on a novel soft-labeling approach. Using the CNN/DailyMail dataset we demonstrate the effectiveness of our approach compared to state-of-the-art extractive-only or abstractive-only baseline methods.

PaperPDFConference PDF

Code

No code repository is listed for this paper in the archive or in Syntology's graph.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

Abstractive Text SummarizationDocument SummarizationSentence

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Abstractive Text Summarization CNN / Daily Mail EditNet ROUGE-1 41.42 #34 of 53 Archive leaderboard report
Abstractive Text Summarization CNN / Daily Mail EditNet ROUGE-2 19.03 #34 of 53 Archive leaderboard report
Abstractive Text Summarization CNN / Daily Mail EditNet ROUGE-L 38.36 #34 of 53 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections