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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 221–230 of 284 papers

TitleStatusHype
Classification and Clustering of Arguments with Contextualized Word EmbeddingsCode0
Classifying Argumentative Relations Using Logical Mechanisms and Argumentation SchemesCode0
A Cascade Model for Argument Mining in Japanese Political Discussions: the QA Lab-PoliInfo-3 Case StudyCode0
AQE: Argument Quadruplet Extraction via a Quad-Tagging Augmented Generative ApproachCode0
ImageArg: A Multi-modal Tweet Dataset for Image Persuasiveness MiningCode0
Spurious Correlations in Cross-Topic Argument MiningCode0
Extracting Arguments from Korean Question and Command: An Annotated Corpus for Structured ParaphrasingCode0
A Streamlined Method for Sourcing Discourse-level Argumentation Annotations from the CrowdCode0
In-Context Learning and Fine-Tuning GPT for Argument MiningCode0
WIBA: What Is Being Argued? A Comprehensive Approach to Argument MiningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified