Our workshop received 39 valid submissions, and accepted 15 papers, with an overall acceptance rate of 38%.

Long Papers

• Answering Naturally : Factoid to Full length Answer Generation, Vaishali Pal, Manish Shrivastava, Irshad Bhat

• Summary Level Training of Sentence Rewriting for Abstractive Summarization, Sanghwan Bae, Taeuk Kim, Jihoon Kim, Sang-goo Lee

• Abstractive Timeline Summarization, Julius Steen and Katja Markert

• Learning to Create Sentence Semantic Relation Graphs for Multi-Document Summarization, Diego Antognini and Boi Faltings

• SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization, Bogdan Gliwa, Iwona Mochol, Maciej Biesek, Aleksander Wawer

• A Closer Look at Data Bias in Neural Extractive Summarization Models, Ming Zhong, Danqing Wang, Pengfei Liu, Xipeng Qiu, Xuanjing Huang

• Global Voices: Crossing Borders in Automatic News Summarization, Khanh Nguyen and Hal Daumé III

Short Papers

• Unsupervised Aspect-Based Multi-Document Abstractive Summarization, Maximin Coavoux, Hady Elsahar, Matthias Galle

• BillSum: A Corpus for Automatic Summarization of US Legislation, Anastassia Kornilova, Vladimir Eidelman

• An Editorial Network for Enhanced Document Summarization, Edward Moroshko, Guy Feigenblat, Haggai Roitman, David Konopnicki

• Towards Annotating and Creating Summary Highlights at Sub-sentence Level, Kristjan Arumae, Parminder Bhatia, Fei Liu

• Multi-Document Summarization with Determinantal Point Processes and Contextualized Representations, Sangwoo Cho, Chen Li, Dong Yu, Hassan Foroosh, Fei Liu

• Analyzing Sentence Fusion in Abstractive Summarization, Logan Lebanoff, John Muchovej, Franck Dernoncourt, Doo Soon Kim, Seokhwan Kim, Walter Chang, Fei Liu

• Summarizing Relationships for Interactive Concept Map Browsers, Abram Handler, Premkumar Ganeshkumar, Brendan O’Connor, Mohamed AlTantawy

• Exploiting Discourse-Level Segmentation for Extractive Summarization, Zhengyuan Liu and Nancy Chen