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 161–170 of 284 papers

TitleStatusHype
DART: a Dataset of Arguments and their Relations on Twitter—0
Dave the debater: a retrieval-based and generative argumentative dialogue agent—0
Decompositional Argument Mining: A General Purpose Approach for Argument Graph Construction—0
Defeasible AceRules: A Prototype—0
Discourse as a Function of Event: Profiling Discourse Structure in News Articles around the Main Event—0
ECHR: Legal Corpus for Argument Mining—0
Efficient argument classification with compact language models and ChatGPT-4 refinements—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
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified