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Common sense is the basic level of practical knowledge that is commonly shared among most people. Such knowledge includes but is not limited to social commonsense (“it’s impolite to comment on people’s weight”), and physical commonsense (“snow is cold”). While humans use commonsense knowledge and reasoning abilities to seamlessly navigate everyday situations, endowing machines with such capabilities has remained an elusive goal of AI research for decades.
Consequently, we organize this workshop to encourage discussion of current progress on building machines with commonsense knowledge and reasoning abilities. We aim to bring together researchers from different areas (e.g. NLP, computer vision, computational neuroscience, psychology) to communicate promising working directions in the area of commonsense reasoning.
Topics of interests include but not limited to
- Methods: methods for commonsense reasoning tasks; methods that integrate commonsense knowledge bases and neural models; methods that improve the interpretability and explainability of neural models for reasoning and more.
- Analysis: methods to probe commonsense knowledge from NLP models; methods to understand reasoning mechanisms of existing models; methods that identify limitations of existing methods for AI applications (including but not limited to NLP, CV and robotics) due to the lack of commonsense knowledge
- Resources: acquiring commonsense knowledge (from text corpora, images, videos, pre-trained neural models, etc.); constructing and completing (semi-)structured CKBs; consolidating CKBs under unified schemas.
- Benchmarks: designing challenging tasks and building datasets to evaluate models’ commonsense knowledge and reasoning abilities; designing new evaluation schemas and metrics forcommonsense reasoning tasks, particularly for openended and generative tasks
The CSRR Workshop will be co-located with ACL 2022!
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We solicit two categories of papers.
- Workshop papers (deadline February 28th AoE): describing new, previously unpublished research in this field. The submissions should follow the ACL-ARR style guidelines. We accept both short (4 pages of content) and long papers (8 pages of content). Submissions will be subject to a double-blind review process (i.e. they need to be anonymized). Final versions of accepted papers will be allowed 1 additional page of content so that reviewer comments can be taken into account.
- Published papers (deadline April 21st AoE): papers on topics relevant to the workshop theme, previously published at NLP or ML conferences. These papers can be submitted in their original format without anonymizing. Submissions will be reviewed for fit to the workshop topics.
In both categories, accepted papers will be:
- published on the workshop website
- presented at the workshop as a lightning talk
Please submit your paper via Openreview: openreview.net/group?id=aclweb.org/ACL/2022/Workshop/CSRR
There will be a Best Paper Award for honoring exceptional papers published at the CSRR workshop, which is sponsored by the Allen Institute for AI.
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Organizers: Antoine Bosselut, Xiang Lorraine Li, Bill Yuchen Lin, Vered Shwartz, Bodhisattwa Prasad Majumder, Yash Kumar Lal, Rachel Rudinger, Xiang Ren, Niket Tandon, Vilém Zouhar