SOTAVerified

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 201–210 of 284 papers

TitleStatusHype
Joker at SemEval-2018 Task 12: The Argument Reasoning Comprehension with Neural Attention—0
Leveraging Small LLMs for Argument Mining in Education: Argument Component Identification, Classification, and Assessment—0
Lexicon Guided Attentive Neural Network Model for Argument Mining—0
Lightly-Supervised Modeling of Argument Persuasiveness—0
LLMs for Argument Mining: Detection, Extraction, and Relationship Classification of pre-defined Arguments in Online Comments—0
Automatic Analysis of Substantiation in Scientific Peer ReviewsCode0
A Bayesian Approach for Sequence Tagging with CrowdsCode0
Boundary Detection and Categorization of Argument Aspects via Supervised LearningCode0
How to Handle Different Types of Out-of-Distribution Scenarios in Computational Argumentation? A Comprehensive and Fine-Grained Field StudyCode0
GRhOOT: Ontology of Rhetorical Figures in GermanCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified