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 31–40 of 284 papers

TitleStatusHype
Efficient argument classification with compact language models and ChatGPT-4 refinements—0
A Hybrid Intelligence Method for Argument Mining—0
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
Exploring the Potential of Large Language Models in Computational ArgumentationCode1
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
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified