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 1–25 of 284 papers

TitleStatusHype
M-Arg: Multimodal Argument Mining Dataset for Political Debates with Audio and TranscriptsCode1
Exploring the Potential of Large Language Models in Computational ArgumentationCode1
Detecting Arguments in CJEU Decisions on Fiscal State AidCode1
LESA: Linguistic Encapsulation and Semantic Amalgamation Based Generalised Claim Detection from Online ContentCode1
Mining Legal Arguments in Court DecisionsCode1
GrASP: A Library for Extracting and Exploring Human-Interpretable Textual PatternsCode1
DebateSum: A large-scale argument mining and summarization datasetCode1
DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language ModelsCode1
LawInstruct: A Resource for Studying Language Model Adaptation to the Legal DomainCode1
Identifying the Human Values behind ArgumentsCode1
Multi-Task Attentive Residual Networks for Argument MiningCode1
Towards an Argument Mining Pipeline Transforming Texts to Argument GraphsCode1
ABCD: A Graph Framework to Convert Complex Sentences to a Covering Set of Simple SentencesCode1
IAM: A Comprehensive and Large-Scale Dataset for Integrated Argument Mining TasksCode1
Argumentative Link Prediction using Residual Networks and Multi-Objective LearningCode1
ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument MiningCode1
AMPERSAND: Argument Mining for PERSuAsive oNline DiscussionsCode1
ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument MiningCode1
Argument Mining Driven Analysis of Peer-ReviewsCode1
Boundary Detection and Categorization of Argument Aspects via Supervised LearningCode0
A Bayesian Approach for Sequence Tagging with CrowdsCode0
How to Handle Different Types of Out-of-Distribution Scenarios in Computational Argumentation? A Comprehensive and Fine-Grained Field StudyCode0
Adapting Serious Game for Fallacious Argumentation to German: Pitfalls, Insights, and Best PracticesCode0
Annotating Arguments in a Corpus of Opinion ArticlesCode0
A Streamlined Method for Sourcing Discourse-level Argumentation Annotations from the CrowdCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified