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 111–120 of 284 papers

TitleStatusHype
A Corpus of Argument Networks: Using Graph Properties to Analyse Divisive Issues—0
ELLIS Alicante at CQs-Gen 2025: Winning the critical thinking questions shared task: LLM-based question generation and selection—0
End-to-End Argumentation Mining in Student Essays—0
A Generative Marker Enhanced End-to-End Framework for Argument Mining—0
End-to-End Argument Mining as Biaffine Dependency Parsing—0
End-to-End Argument Mining for Discussion Threads Based on Parallel Constrained Pointer Architecture—0
Incorporating Zoning Information into Argument Mining from Biomedical Literature—0
Enhancing Investment Opinion Ranking through Argument-Based Sentiment Analysis—0
Advances in Debating Technologies: Building AI That Can Debate Humans—0
Evidence Type Classification in Randomized Controlled Trials—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified