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 61–70 of 284 papers

TitleStatusHype
A Corpus of Annotated Revisions for Studying Argumentative Writing—0
AutoAM: An End-To-End Neural Model for Automatic and Universal Argument Mining—0
Argument Component Classification for Classroom Discussions—0
Argumentative texts and clause types—0
Analyzing Argumentative Discourse Units in Online Interactions—0
Argumentative Stance Prediction: An Exploratory Study on Multimodality and Few-Shot Learning—0
A Corpus of eRulemaking User Comments for Measuring Evaluability of Arguments—0
Can Domain Pre-training Help Interdisciplinary Researchers from Data Annotation Poverty? A Case Study of Legal Argument Mining with BERT-based Transformers—0
Argumentation Synthesis following Rhetorical Strategies—0
Building an Argument Search Engine for the Web—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified