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 11–20 of 284 papers

TitleStatusHype
ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument MiningCode1
GrASP: A Library for Extracting and Exploring Human-Interpretable Textual PatternsCode1
Multi-Task Attentive Residual Networks for Argument MiningCode1
LESA: Linguistic Encapsulation and Semantic Amalgamation Based Generalised Claim Detection from Online ContentCode1
Argument Mining Driven Analysis of Peer-ReviewsCode1
DebateSum: A large-scale argument mining and summarization datasetCode1
Towards an Argument Mining Pipeline Transforming Texts to Argument GraphsCode1
AMPERSAND: Argument Mining for PERSuAsive oNline DiscussionsCode1
Argumentative Link Prediction using Residual Networks and Multi-Objective LearningCode1
Leveraging Context for Multimodal Fallacy Classification in Political DebatesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified