SUKI: Structured and Unstructured Knowledge Integration

Workshop at NAACL 2022 at Seattle, WA on July 14, 2022
Contact: suki-workshop@googlegroups.com

Call for Papers

World knowledge is distributed across diverse resources in either structured (tables, lists, graphs, and databases) or unstructured forms (texts, large pretrained language models). Recently, there have been extensive efforts to represent, inject, and ground knowledge in various NLP tasks. Because many downstream applications require the integration of both structured and unstructured knowledge, it is essential to design more generalized models to handle multiple sources of knowledge inputs. However, recent NLP progress is mostly focused on dealing with homogeneous external knowledge resource in a single form. This workshop aims to bring researchers from different backgrounds together to discuss challenges and promote solutions in NLP techniques for jointly dealing with structured and unstructured knowledge. This draws wide attention from multiple NLP areas such as Information Extraction, Question Answering, Semantic Parsing, Information Retrieval, Fact Verification, Summarization, Data-to-Text Generation, and Conversational AI.

We seek submissions in two tracks:

Research Track. We welcome submissions on research that broadly relates to combining Structured and Unstructured Knowledge on topics including but not limited to:

  • Datasets combining Structured and Unstructured Data
  • Data Augmentation for Structured and Unstructured Data
  • Joint PreTraining for Structured and Unstructured Knowledge
  • Joint Modeling with Structured and Unstructured Knowledge
  • Conversational AI over Structured and Unstructured Knowledge
  • Summarization over Structured and Unstructured Knowledge
  • Language Generation over Structured and Unstructured Knowledge
  • Multilingual Data and Modeling for Structured and Unstructured Knowledge
  • Fairness and Bias in Structured and Unstructured Knowledge
  • Transfer Learning over Structured and Unstructured Knowledge
  • Multitask Learning over Structured and Unstructured Knowledge
  • Human-in-the-loop Learning for Structured and Unstructured Knowledge
  • Human-in-the-loop Evaluation for Models over Structured and Unstructured Knowledge
  • Interpretability for Models over Structured and Unstructured Knowledge

Shared Task Track. We plan to host two shared tasks: UnifiedSKG and FinQA. Please check the shared task page for more information. We accept system descriptions of our shared tasks as non-archival workshop submissions.

Important Dates for the Research Track

  • **April 8, 2022**: Research Track Submission deadline
  • April 15, 2022: Research Track Submission deadline extended!
  • April 15-May 9, 2022: Review period
  • May 13, 2022: Notification of acceptance
  • May 20, 2022: Camera-ready version deadline

Important Dates for the Non-Archival Shared Task Track

  • Feb 15, 2022: Shared Task Launch
  • June 8, 2022: Result Submission Deadline
  • June 15, 2022: System Description Submission Deadline

All deadlines are 11:59 PM UTC -12h (Anywhere on Earth).

Submission Guidelines

Submissions should have at least 4 pages and at most 8 pages of content, plus unlimited pages for references and appendices. Accepted papers will be given 1 additional content page to address reviewers’ comments. Please use the official ARR style files available as an Overleaf template to format your papers. Our reviewing policy is double-blind, and the submissions should be fully anonymized. Please submit through our Openreview submission site.

Dual Submission: We also allow submissions that are under review in other venues or have preprint versions. But please make sure to follow the dual submission policies from the other venues.

Archival vs Non-Archival: During submission, please also indicate if you want your paper to be archival or non-archival. Archival papers, if accepted, will be included in the workshop proceeding, while non-archival will not be included. Both archival or non-archival papers, if accepted, will be presented at workshop.

Anonymity Period: We do not enforce an anonymity period. We allow preprint servers such as arXiv at any point of time.