Supplementary: Document Modeling with External Attention for Sentence Extraction

By Ronald Cardenas, Nikos Papasarantopoulos, Shay B. Cohen, Mirella Lapata, Jiangsheng Yu, Yi Chang. 2018

Subfields: Natural Language Processing, Summarization

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Natural Language Processing

1. Iryna Gurevych
2. Mirella Lapata
3. Yang Gao
4. Mohit Bansal
5. Ido Dagan
6. Shay B. Cohen
7. Christian M. Meyer
8. Graham Neubig

In Summarization

1. Shashi Narayan
2. Christian M. Meyer
3. Iryna Gurevych
4. Mirella Lapata
5. Shay B. Cohen
6. Yang Gao
7. Ryan T. McDonald

Citations in the corpus

• Don’t Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization (2018, methodology): “C OVG , the best performing abstractive system on the CNN/DailyMail datasets, does not do well.”
• Better Rewards Yield Better Summaries: Learning to Summarise Without References (2019, methodology): “…human rating. ated summaries, we invited five users to read and rate the summaries from three systems: NeuralTD+LearnedReward, the Refresh system (Narayan et al., 2018b) and the extractive version of the ExtAbsRL system, which only extracts salient sentences and does not apply sentence…”