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 51–60 of 284 papers

TitleStatusHype
NLAS-multi: A Multilingual Corpus of Automatically Generated Natural Language Argumentation Schemes—0
Can Large Language Models perform Relation-based Argument Mining?—0
End-to-End Argument Mining over Varying Rhetorical StructuresCode0
Automatic Analysis of Substantiation in Scientific Peer ReviewsCode0
Data and models for stance and premise detection in COVID-19 tweets: insights from the Social Media Mining for Health (SMM4H) 2022 shared taskCode0
Overview of ImageArg-2023: The First Shared Task in Multimodal Argument MiningCode0
Argumentative Stance Prediction: An Exploratory Study on Multimodality and Few-Shot Learning—0
TILFA: A Unified Framework for Text, Image, and Layout Fusion in Argument MiningCode0
"I'd Like to Have an Argument, Please": Argumentative Reasoning in Large Language ModelsCode0
AutoAM: An End-To-End Neural Model for Automatic and Universal Argument Mining—0
Show:102550
← PrevPage 6 of 29Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified