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Argument Mining

Argument Mining is a field of corpus-based discourse analysis that involves the automatic identification of argumentative structures in text.

Source: AMPERSAND: Argument Mining for PERSuAsive oNline Discussions

Papers

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Showing 21–30 of 284 papers

TitleStatusHype
ELLIS Alicante at CQs-Gen 2025: Winning the critical thinking questions shared task: LLM-based question generation and selection—0
LLMs for Argument Mining: Detection, Extraction, and Relationship Classification of pre-defined Arguments in Online Comments—0
Towards Comprehensive Argument Analysis in Education: Dataset, Tasks, and Method—0
Exploring new Approaches for Information Retrieval through Natural Language Processing—0
Argument Summarization and its Evaluation in the Era of Large Language Models—0
Leveraging Small LLMs for Argument Mining in Education: Argument Component Identification, Classification, and Assessment—0
On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education—0
Enhancing Rhetorical Figure Annotation: An Ontology-Based Web Application with RAG IntegrationCode0
Natural Language Processing for the Legal Domain: A Survey of Tasks, Datasets, Models, and Challenges—0
CasiMedicos-Arg: A Medical Question Answering Dataset Annotated with Explanatory Argumentative StructuresCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified