The 11th Workshop on Argument Mining

15 July 2024. The ArgMining 2024 program is out! See you in August!

4 July 2024. We are happy to announce our Keynote Speaker: Yufang Hou from IBM Research Europe, Ireland.

17 May 2024. !!! Commitment Deadline Extension !!! 24th of May AOE 31st of May AOE. Commit your paper to ArgMining2024

17 May 2024. !!! Deadline Extension !!! 17th of May AOE 20th of May AOE.

16 May 2024. If you already have your paper reviewed as part of ARR, you can now commit it to ArgMining2024 by the 24th of May AOE!

21 February 2023. The Perspective Argument Retrieval Shared Task launched their Website!

19 February 2023. DialAM Shared Task launched their Website!

7 February 2023. Check the Important Dates! Paper Submission via OpenReview by May 17, 2024

7 February 2023. The 1st Call for Papers is out!

7 February 2023. We are excited to announce the two Shared Tasks @ArgMining2024

7 December 2023. Call for Shared Task is out

7 December 2023. The official ArgMining 2024 website is launched.

Argument Mining (also known as “argumentation mining”) is an emerging research area within computational linguistics that started with focusing on automatically identifying and classifying argument elements, covering several text genres such as legal documents, news articles, online debates, scholarly data, and many more. In recent years, the field (broadly Computational Argumentation) has grown to explore argument quality and synthesis on many levels. The field offers practical uses such as argument-focused search and debating technologies, e.g., IBM Project Debater. The growing interest in computational argumentation has led to several tutorials at major NLP conferences.

While basic tasks such as argument element segmentation and classification are becoming mature, many current and emerging tasks in diverse genres and topics still need to be solved, amidst global polarization and the emergence of Large Language Models.

Program

Panel Session

The Human in Computational Argumentation

This panel session will discuss the role of the human in computational argumentation, exploring ways of creating more representative, fair, and effective computational models of argumentation that better capture the complexities of human discourse. The discussion will focus on two strategies of capturing human context, views, and preferences: perspectivism and personalization. While personalization aims at integrating information about the speaker and target audience (e.g., values and culture) in training or instructing language models, perspectivism aims at ensuring that the views captured by models are representative of the relevant social groups. The panel will look at the consequences, opportunities, and challenges of adapting perspectivism and personalization in computational argumentation.

Keynote Speaker

Yufang Hou, IBM Research Europe - Ireland

Title: Reconstructing Fallacies in Misrepresented Science and Argument Mining in the Wild

Important Dates

• Direct paper submission due (OpenReview): May 17, 2024 May 20, 2024 AOE
• Commitment deadline for ARR papers (OpenReview): May 24, 2024 May 31, 2024 AOE
• Notification of acceptance: June 17, 2024
• Camera-ready papers due: July 1, 2024
• Workshop:August 15, 2024

Submission Topics

The topics for submissions include but are not limited to:

• Identification, Assessment, and Analysis of Arguments
• Identification of argument components (e.g., premises and conclusions)
• Structure analysis of arguments within and across documents
• Relation Identification between arguments and counterarguments (e.g., support and attack)
• 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
• Assessment of arguments with respect to various properties (e.g., stance, clarity)
• Generation of Arguments, Multi-modal and Multi-lingual Argument Mining
• Automatic generation of arguments and their components
• Consideration of discourse goals in argument generation
• Argument mining and generation from multi-modal/multi-lingual data
• Mining and Analysis of different Genres and Domains of Arguments
• Argument mining in specific genres and domains (e.g., education, law, scientific writing)
• Analysis of unique styles within genres (e.g., short informal text, highly structured writing)
• Knowledge Integration, Information Retrieval, and Real-world Applications
• Integration of commonsense and domain knowledge into argumentation models
• Combination of information retrieval methods with argument mining
• Real-world applications, including argument web search, opinion analysis and summarization, and misinformation detection
• Ethical Considerations and Future Reflections
• 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)

CALL FOR PAPERS

The Workshop on Argument Mining provides a regular forum for presenting and discussing cutting-edge research in argument mining (a.k.a argumentation mining) for academic and industry researchers. By continuing a series of ten successful previous workshops, this edition will welcome the submission of long, short, and demo papers. Also, it will feature two shared tasks and a keynote talk.

Submission Details

The organizing committee welcomes submitting long papers, short papers, and demo descriptions. Accepted papers will be presented via oral or poster presentations and included in the ACL 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 at most 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 at most 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 papers must be at most 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.

Multiple Submissions

Submission Format

Submission Link

Double Blind Review

Best Paper Award

Shared Tasks

The Argument Miming Workshop will be hosting two shared tasks.

1. The Perspective Argument Retrieval Shared Task

Organizers : Neele Falk from the University of Stuttgart, and Andreas Waldis from the Ubiquitous Knowledge Processing (UKP) Technical University of Darmstadt, and Infomration System Lab, Lucerne University of Applied Science and Arts.

Overview: The "Perspective Argument Retrieval" task addresses the often-overlooked challenge of incorporating socio-demographic information (such as political views, age, and gender) in argument retrieval. By focusing on these aspects, we acknowledge their potential latent influence on argumentation. With this shared task, we invite the community to develop methods that concentrate on this crucial area and advance state-of-the-art retrieval models by considering the perspective of societal diversity.

All the details regarding the shared task can be found at the Perspective Argument Retrieval Shared Task Website.

2. DialAM-2024: The First Shared Task on Dialogical Argument Mining

Organizers: Ramon Ruiz-Dolz, John Lawrence, Ella Schad and Chris Reed from the Centre for Argument Technology in the University of Dundee.

Overview: With the DialAM-2024 task, we propose the first shared task in dialogue argument mining where argumentation and dialogue information is modelled together in a domain-independent framework. The Inference Anchoring Theory (IAT) framework, makes possible to obtain homogeneous annotations of dialogue argumentation including relevant information and structural data from speech and argumentation, regardless of the domain, and allowing a more complete analysis of argumentation in dialogues together with a consistent cross-domain evaluation of the resulting argument mining systems. The DialAM-2024 consists of two sub-tasks: the identification of propositional (argumentative) relations, and the identification of illocutionary (speech act) relations. For both tasks all the information belonging to argumentation and dialogue will be available for the development of the submitted systems. We invite the community to participate in the DialAM-2024 task and explore how the use of additional information from the dialogue can be integrated into the argument mining process, in an attempt to take a step forward from sequence modelling approaches, where much of the relevant information to argumentation remains implicit behind the natural language.

• Task 1: Identification of Propositional Relations: In the first task, the goal is to detect argumentative relations existing between the propositions identified and segmented in the argumentative dialogue. Such relations are: Inference (RA), Confclict (CA), and Rephrase (MA).
• Task 2: Identification of Illocutionary Relation:In the second task, the goal is to detect illocutionary relations existing between locutions uttered in the dialogue and and the argumentative propositions associated with them such as: Asserting, Agreeing, Arguing, or Disagreeing among others.

All the details regarding the shared task can be found at the DialAM Shared Task Website.

Committee

Organizing Committee

Yamen Ajjour

Roy Bar-Haim

Roxanne El Baff

Zhexiong Liu

Gabriella Skitalinskaya

Program Committee

Past Workshops

Policy

We abide by the ACL anti-harassment policy.