Controllable-Summarization-Paper-List

A summary of must-read papers for Controllable Summarization.

• Contributed by Yixi Ding

Please follow this link to view papers in chronological order.

Content

1. Survey
2. Models
3. Applications
3.1 Length Controllable Summrization	3.2 Language Controllable Summrization
3.3 Content Controllable Summrization
4. Evaluation
5. Resources

Survey papers

Models

1. Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization EMNLP, 2018. paper github link

   Shashi Narayan, Shay B. Cohen, Mirella Lapata

Applications

Generic Controllable Summarization

1. CTRLsum: Towards Generic Controllable Text Summarization arXiv preprint, 2020.

   Junxian He, Wojciech Kryściński, Bryan McCann, Nazneen Rajani, Caiming Xiong

Length Controllable Summarization

This direction is about generating summaries within a specific length.

1. Length-controllable Abstractive Summarization by Guiding with Summary Prototype arXiv preprint, 2020. paper

   Itsumi Saito, Kyosuke Nishida, Kosuke Nishida, Atsushi Otsuka, Hisako Asano, Junji Tomita, Hiroyuki Shindo, Yuji Matsumoto

2. Length Control in Abstractive Summarization by Pretraining Information ACL, 2022. paper

   Yizhu Liu, Qi Jia, Kenny Zhu

Language Controllable Summarization

This direction is about generating summaries for layman or experts.

1. TLDR: Extreme Summarization of Scientific Documents ACL, 2020. paper dataset

   Isabel Cachola, Kyle Lo, Arman Cohan, Daniel Weld

Content Controllable Summarization

This direction is about generating summaries based on specific entities or keywords.

1. Planning with Learned Entity Prompts for Abstractive Summarization TACL, 2021. paper

   Shashi Narayan, Yao Zhao, Joshua Maynez, Gonçalo Simões, Vitaly Nikolaev, Ryan McDonald

Evaluation

Resources

Controllable summarization datasets and toolkits.

1. LongSumm dataset

2. Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization EMNLP, 2018. paper dataset

   Shashi Narayan, Shay B. Cohen, Mirella Lapata

3. TLDR: Extreme Summarization of Scientific Documents ACL, 2020. paper dataset

   Isabel Cachola, Kyle Lo, Arman Cohan, Daniel Weld

4. TLDR9+: A Large Scale Resource for Extreme Summarization of Social Media Posts ACL Workshop, 2021. paper dataset

   Sajad Sotudeh, Hanieh Deilamsalehy, Franck Dernoncourt, Nazli Goharian

5. Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature EMNLP, 2022. paper github link

   Tomas Goldsack, Zhihao Zhang, Chenghua Lin, Carolina Scarton

6. ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networks AAAI, 2019. paper github link

   Michihiro Yasunaga, Jungo Kasai, Rui Zhang, Alexander R. Fabbri, Irene Li, Dan Friedman, Dragomir R. Radev