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 31–40 of 284 papers

TitleStatusHype
A Comprehensive and Large-Scale Dataset for Integrated Argument Mining Tasks—0
Argument Mining for Understanding Peer Reviews—0
A News Editorial Corpus for Mining Argumentation Strategies—0
An Empirical Study on Measuring the Similarity of Sentential Arguments with Language Model Domain Adaptation—0
A Cascade Model for Proposition Extraction in Argumentation—0
An Argument-Annotated Corpus of Scientific Publications—0
ArgumenText: Searching for Arguments in Heterogeneous Sources—0
Analyzing the Semantic Types of Claims and Premises in an Online Persuasive Forum—0
Active Learning for Argument Mining: A Practical Approach—0
TACAM: Topic And Context Aware Argument Mining—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified