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 241–250 of 284 papers

TitleStatusHype
Contextual Argument Component Classification for Class Discussions—0
Contextual stance classification of opinions: A step towards enthymeme reconstruction in online reviews—0
Corpus for Modeling User Interactions in Online Persuasive Discussions—0
Corpus Wide Argument Mining -- a Working Solution—0
Cross-Genre Argument Mining: Can Language Models Automatically Fill in Missing Discourse Markers?—0
Cross-topic Argument Mining from Heterogeneous Sources Using Attention-based Neural Networks—0
Cross-topic Argument Mining from Heterogeneous Sources—0
CRST: a Claim Retrieval System in Twitter—0
DART: a Dataset of Arguments and their Relations on Twitter—0
Dave the debater: a retrieval-based and generative argumentative dialogue agent—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified