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 141–150 of 284 papers

TitleStatusHype
Transformer-Based Models for Automatic Identification of Argument Relations: A Cross-Domain Evaluation—0
DebateSum: A large-scale argument mining and summarization datasetCode1
Aspect-Based Argument MiningCode0
Multilingual Argument Mining: Datasets and Analysis—0
Extracting Implicitly Asserted Propositions in ArgumentationCode0
Discourse as a Function of Event: Profiling Discourse Structure in News Articles around the Main Event—0
Towards Better Non-Tree Argument Mining: Proposition-Level Biaffine Parsing with Task-Specific Parameterization—0
Towards an Argument Mining Pipeline Transforming Texts to Argument GraphsCode1
The Discussion Tracker Corpus of Collaborative Argumentation—0
Unsupervised Argumentation Mining in Student Essays—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified