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 171–180 of 284 papers

TitleStatusHype
Neural-Symbolic Argumentation Mining: an Argument in Favor of Deep Learning and Reasoning—0
Fine-Grained Argument Unit Recognition and ClassificationCode0
Argument Mining for Understanding Peer Reviews—0
Combining Deep Learning and Argumentative Reasoning for the Analysis of Social Media Textual Content Using Small Data Sets—0
A Bayesian Approach for Sequence Tagging with CrowdsCode0
Argumentative Link Prediction using Residual Networks and Multi-Objective LearningCode1
Evidence Types, Credibility Factors, and Patterns or Soft Rules for Weighing Conflicting Evidence: Argument Mining in the Context of Legal Rules Governing Evidence Assessment—0
An Argument-Annotated Corpus of Scientific Publications—0
Annotating Claims in the Vaccination Debate—0
ArguminSci: A Tool for Analyzing Argumentation and Rhetorical Aspects in Scientific WritingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified