Papers with Argument Mining

11 papers
Advances in Debating Technologies: Building AI That Can Debate Humans (2021.acl-tutorials)

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Challenge: This tutorial focuses on Debating Technologies, a sub-field of computational argumentation defined as "computational technologies developed directly to enhance, support, and engage with human debating" the tutorial provides a holistic view of a debated system, and discusses practical applications and future challenges of debation technologies.
Approach: They present a tutorial on Debating Technologies, a sub-field of computational argumentation . they introduce Project Debater, which is the first AI system to debate human experts .
Outcome: The project Debater is the first AI system to debate human experts on complex topics.
Before Name-Calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation (N18-1)

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Challenge: Existing research lacks solid empirical investigation of typology of ad hominem arguments and their potential causes.
Approach: They propose to perform several large-scale annotation studies and experiment with various neural architectures to validate hypotheses such as controversy or reasonableness.
Outcome: The proposed model identifies the ad hominem fallacy and its possible causes using explainable neural network architectures.
Open-Mindedness and Style Coordination in Argumentative Discussions (2021.eacl-main)

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Challenge: Previous research has shown that linguistic accommodation correlates with gaps in the power and status of the speakers and the way it promotes approval and discussion efficiency.
Approach: They propose a novel perspective on linguistic accommodation, exploring its correlation with the open-mindedness of a speaker, rather than to her social status.
Outcome: The proposed approach improves the open-mindedness of a speaker and lowers discussion efficiency.
Annotating Arguments in a Corpus of Opinion Articles (2022.lrec-1)

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Challenge: Argument annotation is the process of exposing and justifying one's points of view, with the aim of conveying a logical reasoning through a set of semantically related propositions.
Approach: They propose to use argumentative discourse units to annotate arguments in Portuguese using a multi-layered process to analyze the annotations produced.
Outcome: The proposed model exploits the best practices identified in previous studies while fostering the potential use of the resulting annotated corpus for new purposes.
Analyzing the Persuasive Effect of Style in News Editorial Argumentation (2020.acl-main)

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Challenge: Existing research has investigated the persuasive effect of content and style on argumentative content.
Approach: They compare the style of news editorials with ideology-specific effect annotations to find out how important it is to achieve persuasiveness.
Outcome: The proposed method shows that conservative readers are resistant to style on liberal editorials, whereas conservative readers resist style on conservatives.
TRopBank: Turkish PropBank V2.0 (2020.lrec-1)

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Challenge: PropBank is a hand-annotated corpus of propositions used to obtain predicate-argument information of a language.
Approach: They present TRopBank "Turkish PropBank v2.0" which is a hand-annotated corpus of propositions . it is used to obtain the predicate-argument information of a language .
Outcome: The proposed annotations provide the predicate-argument information of a language . the proposed annotation is based on the annotations of 17.673 verbs in Turkish .
CEAMC: Corpus and Empirical Study of Argument Analysis in Education via LLMs (2024.findings-emnlp)

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Challenge: Existing argument component classifications in education are simplistic and isolated, failing to capture the complete argument information.
Approach: They propose to annotate a manually annotated argument component classification dataset from authentic examination settings and to explore the performance of Large Language Models on CEAMC.
Outcome: The proposed dataset can be used to analyze argumentative essays in education.
Towards Comprehensive Argument Analysis in Education: Dataset, Tasks, and Method (2025.acl-long)

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Challenge: Existing research on argument mining has proposed various argument annotation schemes and tasks.
Approach: They propose a framework comprising 14 fine-grained relation types to capture the interplay between argument components for a thorough understanding of argument structure.
Outcome: The proposed framework captures the interplay between argument components for a thorough understanding of argument structure.
Exploring the Role of Argument Structure in Online Debate Persuasion (2020.emnlp-main)

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Challenge: Existing work in NLP has shown that linguistic features extracted from debate text and features encoding the characteristics of the audience are both critical in persuasion studies.
Approach: They propose to incorporate argument structure features into an LSTM-based model to assess the persuasiveness of debates.
Outcome: The proposed model incorporates argument structure features to predict debaters that make the most convincing arguments on online debate forums.
Lemmatising Verbs in Middle English Corpora: The Benefit of Enriching the Penn-Helsinki Parsed Corpus of Middle English 2 (PPCME2), the Parsed Corpus of Middle English Poetry (PCMEP), and A Parsed Linguistic Atlas of Early Middle English (PLAEME) (2020.lrec-1)

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Challenge: Using the lemmatisation of three annotated corpora of Middle English, we hypothesize that verbs copied from Old French favoured and produced grammatical changes in ME . instead of using the more traditional and more problematic term 'borrowing' we use Johanson's term . copying allows for the non-identicality of original and copied material.
Approach: They propose to lemmatise the Penn-Helsinki Parsed Corpus of Middle English 2 (PPCME2), the Parsed corpus of middle english poetry (PCMEP) and A Parsed Linguistic Atlas of Early Middle English (PLAEME) they hypothesize that verbs copied from Old French favoured and produced grammatical changes in ME .
Outcome: The proposed method improves accuracy and recall of the annotated corpus of Middle English and the PLAEME.
When Argumentation Meets Cohesion: Enhancing Automatic Feedback in Student Writing (2024.lrec-main)

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Challenge: Argumentative essays require a high degree of cohesion, defined as a network of semantic relationships that link together.
Approach: They investigate the role of arguments in the automatic scoring of cohesion in argumentative essays.
Outcome: The proposed model improves on a multi-task learning process by adding argumentative elements as an auxiliary task.

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