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 81–90 of 284 papers

TitleStatusHype
On Selecting Training Corpora for Cross-Domain Claim Detection—0
SMM4H 2022 Task 2: Dataset for stance and premise detection in tweets about health mandates related to COVID-19—0
Transferring Confluent Knowledge to Argument MiningCode0
Boundary Detection and Categorization of Argument Aspects via Supervised LearningCode0
Will It Blend? Mixing Training Paradigms & Prompting for Argument Quality Prediction—0
ImageArg: A Multi-modal Tweet Dataset for Image Persuasiveness MiningCode0
Transfer Learning of Lexical Semantic Families for Argumentative Discourse Units Identification—0
EDU-AP: Elementary Discourse Unit based Argument ParserCode0
AntCritic: Argument Mining for Free-Form and Visually-Rich Financial Comments—0
A Cascade Model for Argument Mining in Japanese Political Discussions: the QA Lab-PoliInfo-3 Case StudyCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified