Background and Scope
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While interest in automatic approaches to Counterspeech generation has been steadily growing, including studies on data curation (Chung et al., 2019a; Fanton et al., 2021), detection (Chung et al., 2021a; Mathew et al., 2018), and generation (Tekiroglu et al., 2020; Chung et al., 2021b; Zhu and Bhat, 2021; Tekiroglu et al., 2022), the large majority of the published experimental work on automatic Counterspeech generation has been carried out for English. This is due to the scarcity of both non-English manually curated training data and to the crushing predominance of English in the generative Large Language Models (LLMs) ecosystem. A workshop on exploring Multilingual Counterspeech Generation is proposed to promote and encourage research on multilingual approaches for this challenging topic.
Thus, this workshop aims to test monolingual and multilingual LLMs in particular and Language Technology in general to automatically generate counterspeech not only in English but also in languages with fewer resources. In this sense, an important goal of the workshop will be to understand the impact of using LLMs, considering for example how to deal with pressing issues such as biases, hallucinated content, data scarcity or data contamination.
We seek to maximize the scientific and social impact of this workshop by promoting the creation of a community of researchers from diverse fields, such as computer and social sciences, as well as policy makers and other stakeholders interested in automatic counterspeech generation. By doing so we aim to gain a deeper understanding of how counterspeech is currently used to tackle abuse by individuals, activists, and organizations and how Natural Language Processing (NLP) and Generation (NLG) may be best applied to counteract it.
Call for Papers
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We welcome submissions on the following topics (but not limited to):
- Models and methods for generating counterspeech in different languages.
- Automatic Counterspeech generation for low resource languages with scarce training data.
- Dialogue agents that use counterspeech to combat offensive messages that are directed to individuals or groups, targeted based on various aspects such as ideology, gender, sexual orientation and religion.
- Methods for human and automatic evaluation of counterspeech.
- Multidisciplinary studies providing different perspectives on the topic such as computer science, social science, psychology, etc.
- Development of taxonomies and quality datasets for counterspeech in multiple languages.
- Potentials and limitations (e.g., fairness, biases, hallucinated content) of applying different NLP methods, such as LLMs, to generate counterspeech.
- Social impact and empirical studies of counterspeech in social networks, including research on the effectiveness and consequences for users of using counterspeech to combat hate online.
Submission
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We welcome two types of papers: regular workshop papers and non-archival submissions. Regular workshop papers will be included in the workshop proceedings. All submissions must be in PDF format and made through START [https://softconf.com/coling2025/MCG25/]
- Regular workshop papers: Authors can submit papers up to 8 pages, with unlimited pages for references. Authors may submit up to 100 MB of supplementary materials separately and their code for reproducibility. All submissions undergo an double-blind single-track review. Accepted papers will be presented as posters with the possibility of oral presentations.
- Non-archival submissions: Cross-submissions are welcome. Accepted papers will be presented at the workshop, but will not be included in the workshop proceedings. Papers must be in PDF format and will be reviewed in a double-blind fashion by workshop reviewers. We also welcome extended abstracts (up to 2 pages) of papers that are work in progress, under review or to be submitted to other venues. Papers in this category need to follow the COLING format.
Important Dates
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- Submission: November 25th, 2024
- Notification of Acceptance: December 8th, 2024
- Camera-Ready Papers Due: December 13th, 2024