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 161–170 of 284 papers

TitleStatusHype
The Swedish PoliGraph: A Semantic Graph for Argument Mining of Swedish Parliamentary Data—0
TACAM: Topic And Context Aware Argument Mining—0
Towards a Holistic View on Argument Quality Prediction—0
Towards an argumentative content search engine using weak supervision—0
Towards Argument Mining for Social Good: A Survey—0
Towards Better Non-Tree Argument Mining: Proposition-Level Biaffine Parsing with Task-Specific Parameterization—0
Towards Comprehensive Argument Analysis in Education: Dataset, Tasks, and Method—0
Towards Feasible Guidelines for the Annotation of Argument Schemes—0
Toward Stance Classification Based on Claim Microstructures—0
Transfer Learning of Lexical Semantic Families for Argumentative Discourse Units Identification—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified