CALL FOR ARR Commitment The 10th Workshop on Argument Mining @ EMNLP 2023 December 7, 2023

https://argmining-org.github.io/2023/

The 10th Workshop on Argument Mining will be held on December 7, 2023 in Singapore together with EMNLP 2023. This will be a hybrid event.

ArgMining 2023 will accept submissions of ARR-reviewed papers, provided that the ARR reviews and meta-reviews are available by the ARR commitment deadline (September 25).

The Workshop on Argument Mining provides a regular forum for the presentation and discussion of cutting-edge research in argument mining (a.k.a argumentation mining) to both academic and industry researchers. By continuing a series of nine successful previous workshops, this edition will welcome the submission of long, short, and demo papers. It will feature two shared tasks, a panel on the last ten years of Argument Mining, and a keynote talk.

IMPORTANT DATES

Paper commitment from ARR: September 25, 2023 Notification of acceptance: October 7, 2023 Camera-ready submission: October 18, 2023 Workshop: December 7, 2023

TOPICS OF INTEREST

The topics for submissions include but are not limited to: Automatic identification of argument components (e.g., premises and conclusions), the structure in which they form an argument, and relations between arguments and counterarguments (e.g., support and attack) in as well as across documents Automatic assessment of arguments and argumentation with respect to various properties, such as stance, clarity, and persuasiveness Automatic generation of arguments and their components, including the consideration of discourse goals (e.g., stages of a critical discussion or rhetorical strategies) Creation and evaluation of argument annotation schemes, relationships to linguistic and discourse annotations, (semi-) automatic argument annotation methods and tools, and creation of argumentation corpora Argument mining in specific genres and domains (e.g., social media, education, law, and scientific writing), each with a unique style (e.g., short informal text, highly structured writing, and long-form documents) Argument mining and generation from multi-modal and/or multilingual data Integration of commonsense and domain knowledge into argumentation models for mining and generation Combination of information retrieval methods with argument mining, e.g., in order to build the next generation of argumentative (web) search engines Real-world applications, including argument web search, opinion analysis in customer reviews, argument analysis in meetings, misinformation detection Perspectivist approaches to subjective argument mining tasks for which multiple ”ground truths” may exist, including multi-perspective machine learning and the creation of non-aggregated datasets Reflection on the ethical aspects and societal impact of argument mining methods Reflection on the future of argument mining in light of the fast advancement of large language models (LLMs).

SUBMISSIONS

The organizing committee welcomes the submission of long papers, short papers, and demo descriptions. Accepted papers will be presented either via oral or poster presentations. They will be included in the EMNLP proceedings as workshop papers. - Long paper submissions must describe substantial, original, completed, and unpublished work. Wherever appropriate, concrete evaluation and analysis should be included. Long papers must be no longer than eight pages, including title, text, figures and tables. An unlimited number of pages is allowed for references. Two additional pages are allowed for appendices, and an extra page is allowed in the final version to address reviewers’ comments. - Short paper submissions must describe original and unpublished work. Please note that a short paper is not a shortened long paper. Instead, short papers should have a point that can be made in a few pages, such as a small, focused contribution; a negative result; or an interesting application nugget. Short papers must be no longer than four pages, including title, text, figures and tables. An unlimited number of pages is allowed for references. One additional page is allowed for the appendix, and an extra page is allowed in the final version to address reviewers’ comments. - Demo descriptions must be no longer than four pages, including title, text, examples, figures, tables, and references. A separate one-page document should be provided to the workshop organizers for demo descriptions, specifying furniture and equipment needed for the demo.

Submission Format All long, short, and demonstration submissions must follow the two-column EMNLP 2023 format. Authors are expected to use the LaTeX or Microsoft Word style template (https://2023.emnlp.org/calls/style-and-formatting/). Submissions must conform to the official EMNLP style guidelines, which are contained in these templates. Submissions must be electronic, in PDF format.

Submission Link Authors have to fill in the submission form in the START system indicating relevant information to their ARR paper before September 25, 2023, 11:59 pm UTC-12h (anywhere on earth). https://softconf.com/emnlp2023/ArgMining2023/

Double Blind Review ArgMining 2023 will follow the ACL policies for preserving the integrity of double-blind review for long and short paper submissions. Papers must not include authors’ names and affiliations. Furthermore, self-references or links (such as github) that reveal the author’s identity, e.g., “We previously showed (Smith, 1991) …” must be avoided. Instead, use citations such as “Smith previously showed (Smith, 1991) …” Papers that do not conform to these requirements will be rejected without review. Papers should not refer, for further detail, to documents that are not available to the reviewers. For example, do not omit or redact important citation information to preserve anonymity. Instead, use third person or named reference to this work, as described above (“Smith showed” rather than “we showed”). If important citations are not available to reviewers (e.g., awaiting publication), these paper/s should be anonymised and included in the appendix. They can then be referenced from the submission without compromising anonymity. Papers may be accompanied by a resource (software and/or data) described in the paper, but these resources should also be anonymized. Unlike long and short papers, demo descriptions will not be anonymous. Demo descriptions should include the authors’ names and affiliations, and self-references are allowed.

BEST PAPER AWARDS In order to recognize significant advancements in argument mining science and technology, ArgMining 2023 will include best paper awards. All papers at the workshop are eligible for the best paper awards and a selection committee consisting of prominent researchers in the fields of interest will select the recipients of the awards.

ArgMining 2023 ORGANIZING COMMITTEE

Milad Alshomary, Leibniz University Hannover, Germany Chung-Chi Chen, National Institute of Advanced Industrial Science and Technology, Japan Smaranda Muresan, Columbia University, USA Joonsuk Park, University of Richmond, USA Julia Romberg, Heinrich Heine University of Duesseldorf, Germany