Proceedings of the 11th Workshop on Argument Mining (ArgMining 2024)

Abstract

Argument Mining (“argumentation mining”) is an emerging research area within computational linguistics. It initially focused on automatically identifying and classifying argument elements across various text genres.

In the recent years, the field has expanded to explore argument quality and synthesis on multiple levels. This growth has led to the development of practical applications such as argument-focused search and debating technologies, exemplified by IBM Project Debater. The increasing interest in computational argumentation has resulted in the organization of several tutorials at major NLP conferences, providing a wealth of knowledge and insights to the community. While basic tasks such as argument element segmentation and classification are maturing, 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. The ArgMining community is constantly growing, as demonstrated by the increasing number of submissions on argument mining being accepted at top-level international conferences in NLP and AI. This year’s 11th edition of the workshop allowed the submission of long, short, and demo papers for the main workshop track. Also, ArgMining2024 hosted two shared tasks as part of the workshop: The Perspective Argument Retrieval Shared Task and DialAM-2024: The First Shared Task on Dialogical Argument Mining. We had 28 valid paper submissions; 16 were for the main workshop (13 long, 3 short), and 12 were for the two shared tasks (5 short and 1 overview long paper for each). The submissions came from institutions in 11 countries. For the main workshop, we accepted 6 long papers and 1 short paper (44% acceptance rate compared to 41% for last year’s ArgMining 2023). All accepted papers are included in the proceedings.