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
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