News

August 8th: For presentation format, posters will use A0 landscape, each long talk is 16 minutes plus 4 minutes QA, and each short talk is 12 minutes plus 3 minutes QA.

August 7th: Accepted paper lists and workshop schedule are out!

July 21st: Camera ready deadline is extended to July 28th, 2017

July 10th: Notification emails sent out to the authors! Our workshop has an acceptance rate of 60%. For camera-ready version, please use the EMNLP 2017 template. One extra page is allowed for both long papers and short papers.

June 9th: Submission deadline extended to June 12th, 2017

June 1st: Submission deadline extended to June 10th, 2017

Overview

Can intelligent systems be devised to create concise, fluent, and accurate summaries from vast amounts of data? Researchers have strived to achieve this goal in the past fifty years, starting from the seminal work of Luhn (1958) on automatic text summarization. Existing research includes the development of extractive and abstractive summarization technologies, evaluation metrics (e.g., ROUGE and Pyramid), as well as the construction of benchmark datasets and resources (e.g., annual competitions such as DUC (2001-2007), TAC (2008-2011), and TREC (2014-2016 on Microblog/Temporal Summarization)).

The goal for this workshop is to provide a research forum for cross-fertilization of ideas. We seek to bring together researchers from a diverse range of fields (e.g., summarization, visualization, language generation, cognitive and psycholinguistics) for discussion on key issues related to automatic summarization. This includes discussion on novel paradigms/frameworks, shared tasks of interest, information integration and presentation, applied research and applications, and possible future research foci. The workshop will pave the way towards building a cohesive research community, accelerating knowledge diffusion, developing new tools, datasets and resources that are in line with the needs of academia, industry, and government.

Topics

  • Abstractive and extractive summarization
  • Language generation
  • Multiple text genres (News, tweets, product reviews, meeting conversations, forums, lectures, student feedback, emails, medical records, books, research articles, etc)
  • Multimodal Input: Information integration and aggregation across multiple modalities (text, speech, image, video)
  • Multimodal Output: Summarization and visualization + interactive exploration
  • Tailoring summaries to user queries or interests
  • Semantic aspects of summarization (e.g. semantic representation, inference, validity)
  • Development of new algorithms
  • Development of new datasets and annotations
  • Development of new evaluation metrics
  • Cognitive or psycholinguistic aspects of summarization and visualization (e.g. perceived readability, usability, etc)
  • Invited Speakers

  • Katja Filippova (Google Research, Switzerland)
  • Andreas Kerren (Linnaeus University, Sweden)
  • Ani Nenkova (University of Pennsylvania, USA)
  • Organizers

  • Lu Wang (Northeastern University, USA)
  • Giuseppe Carenini (University of British Columbia, Canada)
  • Jackie Chi Kit Cheung (McGill University, Canada)
  • Fei Liu (University of Central Florida, USA)
  • Contact

    Should you have any question or suggestion, please feel free to send emails to luwang@ccs.neu.edu (Lu Wang).

    This workshop follows ACL Anti-Harassment Policy.