Papers with argumentative components

7 papers
AQE: Argument Quadruplet Extraction via a Quad-Tagging Augmented Generative Approach (2023.findings-acl)

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Challenge: Argument mining involves multiple subtasks, but each one is insufficient for understanding argumentative structure and reasoning process.
Approach: They propose a quadruplet extraction task that extracts four argumentative components . they use a generative quadragging module to augment the training of the generative framework .
Outcome: The proposed method can extract arguments from a large-scale dataset.
Corpus for Modeling User Interactions in Online Persuasive Discussions (2020.lrec-1)

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Challenge: Several studies have focused on the identification and classification of argumentative components and the argumentative relations between the components.
Approach: They propose an annotation scheme and corpus that captures user-generated inner-post arguments and inter-post relations between users in ChangeMyView.
Outcome: The proposed annotation scheme captures user-generated inner-post arguments and inter-post relations in ChangeMyView, a persuasive forum.
Yes, we can! Mining Arguments in 50 Years of US Presidential Campaign Debates (P19-1)

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Challenge: Political debates are a natural application scenario for Argument Mining.
Approach: They propose an argument mining approach to political debates that uses argument components to annotate 39 political debate from the last 50 years of US presidential campaigns.
Outcome: The proposed approach outperforms baselines in argument mining over political debates.
Budget Argument Mining Dataset Using Japanese Minutes from the National Diet and Local Assemblies (2022.lrec-1)

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Challenge: Budget argument mining attempts to identify argumentative components related to a budget item . argument mining is a subtask of QA Lab-PoliInfo-3 in NTCIR-16 .
Approach: They propose a dataset to link budget information to minutes and budget items . they describe the construction of the dataset and the annotation procedure .
Outcome: The proposed dataset is based on a QA Lab-PoliInfo-3 subtask . it identifies argumentative components related to a budget item and classifies them .
Argument-based Detection and Classification of Fallacies in Political Debates (2023.emnlp-main)

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Challenge: Fallacies are arguments that employ faulty reasoning, causing inaccurate conclusions and invalid inferences . ad hominem fallacy is one of the most common fallacy labels used in political debates despite its use in many scenarios .
Approach: They extend the ElecDeb60To16 dataset of U.S. presidential debates annotated with fallacious arguments by incorporating the most recent Trump-Biden debate.
Outcome: The proposed method extends the ElecDeb60To16 dataset of U.S. presidential debates annotated with fallacious arguments .
Argument mining as a multi-hop generative machine reading comprehension task (2023.findings-emnlp)

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Challenge: Argument mining is a natural language processing task that aims to generate an argumentative graph given an unstructured argumentative text.
Approach: They propose a new approach which transfers the argument mining task into a multi-hop reading comprehension task by incorporating a "chain of thought" information into the model.
Outcome: The proposed approach surpasses SOTA results on two arguments mining benchmarks.
Segmentation of Complex Question Turns for Argument Mining: A Corpus-based Study in the Financial Domain (2024.lrec-main)

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Challenge: Earnings Conference Calls (ECCs) are a favoured domain for the study of argumentation in context and the extraction of Argumentative Discourse Units (ADUs).
Approach: Earnings Conference Calls (ECCs) are favoured domain for study of argumentation in context and extraction of Argumentative Discourse Units (ADUs).
Outcome: ECCs are favoured for study of argumentation in context and extraction of Argumentative Discourse Units (ADUs).

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