Welcome to 1st DialDoc Workshop at ACL-IJCNLP 2021!

Goal-oriented conversational systems can unlock a vast amount of information in the associated documents, in which written and visual content dominate the way that individuals and organizations choose to present their interests and knowledge to the world. We posit that one scalable way to create personalized conversational systems is to have them arise directly from such content. There are significant individual research threads that show promises in handling heterogeneous knowledge embedded in the documents, including (1) unstructured content such as text passages (CoQA, QuAC, ShARC, DoQA); (2) semi-structured content such as tables or lists (SQA, HybridQA); (3) multimedia such as images and videos with associated textual descriptions (RecipeQA, PsTuts-VQA); (4) or structured data specified by schema such as RDFa or Microdata in the webpages. The purpose of this workshop on Document-grounded Dialogue and Conversational QA is to invite researchers to bring their individual perspectives on the subject, and to advance the field in joint effort by providing a shared task and competition.

Call for Papers

We welcome submissions of original work as long or short papers as well as non-archival papers. All accepted papers will be presented at the workshop.

Topics of interest
We encourage submissions from a wide range of topics, including but not limited to:
  • Document-grounded dialogue systems
  • Conversational machine reading comprehension
  • Machine reading comprehension / contextual QA / sequential QA over documents
  • Conversational search among domain documents
  • Topical chat based on associated documents
  • Parsing semi-structured document content for sequential QA or dialogue / table reading
  • Policy learning for document-guided dialogue agents
  • Task-oriented knowledge-grounded multimodal dialogue
    • task-oriented situated dialogue
    • task-oriented domain-knowledge-grounded VQA
    • task-oriented video-based dialogue
  • Evaluations for document-grounded dialogue
  • Transfer learning for document-grounded dialogue systems on low-resource domains
  • Summarization of document-grounded dialogues
  • Model interpretation of document-grounded dialogues
Submission Details

Submission tracks:
There will be following tracks: the main research track ("regular long paper", "regular short paper") and technical system track (shared task).

To submit your paper, please use Softconf link.

Formatting Guidelines:
We accept long (eight pages plus unlimited references) and short (four pages plus unlimited references) papers, which should conform to ACL submission information.

Non-Archival Submissions:
The accepted papers can opt to be non-archival, i.e., the work could be published elsewhere before or after the workshop.

Review Process
All submissions will be peer-reviewed by at least two reviewers. The reviewing process will be double-blinded at the level of the reviewers. Authors are responsible for anonymizing the submissions

Important Dates

  • Workshop Paper Due Date: April 26, 2021 (AoE)   → May 6, 2021 (AoE)
  • Notification of Acceptance: May 28, 2021 (AoE)   → June 1, 2021 (AoE)
  • Camera-ready papers due: June 7, 2021 (AoE)
  • Workshop Dates: August 5, 2021

Invited Speakers

Jonathan Berant (Tel-Aviv University)
Danqi Chen (Princeton University)
Raquel Fernández (University of Amsterdam)
Dilek Hakkani-Tur (Amazon Alexa AI)
Sebastian Riedel (University College London)
Verena Rieser (Heriot-Watt University)
Jason Weston (Facebook AI Research)
William Wang Yang (University of California, Santa Barbara)
Scott (Wen-tau) Yih (Facebook AI Research)

Program Committee

Amanda Buddemeyer (University of Pittsburgh)
Asli Celikyilmaz (Microsoft Research)
Chengguang Tang (Alibaba DAMO)
Chulaka Gunasekara (IBM Research AI)
Danish Contractor (IBM Research AI)
Dian Yu (Tencent)
Diane Litman (University of Pittsburgh)
Ehud Reiter (University of Aberdeen)
Elizabeth Clark (University of Washington)
Eunsol Choi (University of Texas at Austin)
Hanjie Chen (University of Virginia)
Hareesh Ravi (Rutgers University)
Hui Wan (IBM Research AI)
Ioannis Konstas (Heriot-Watt University)
Jonathan Herzig (Tel-Aviv University)
Matthew Stone (Rutgers University)
Mert Inan (University of Pittsburgh)
Michael Johnston (Interactions)
Minjoon Seo (KAIST)
Mo Yu (IBM Research AI)
Peng Qi (Stanford University)
Ravneet Singh (University of Pittsburgh)
Ryuichi Takanobu (Tsinghua University)
Seokhwan Kim (Amazon Alexa AI)
Shehzaad Dhuliawala (Microsoft Research Montreal)
Srinivas Bangalore (Interactions)
Vaibhav Adlakha (McGill and Mila)
Xiaoxiao Guo (IBM Research AI)


Malihe Alikhani (University of Pittsburgh)
Song Feng (IBM Research)
He He (New York University)
Mohit Iyyer (University of Massachusetts Amherst)
Yangfeng Ji (University of Virginia)
Siva Reddy (McGill University, MILA)
Zhou Yu (Columbia University)