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 1–25 of 284 papers

TitleStatusHype
LawInstruct: A Resource for Studying Language Model Adaptation to the Legal DomainCode1
Exploring the Potential of Large Language Models in Computational ArgumentationCode1
Detecting Arguments in CJEU Decisions on Fiscal State AidCode1
ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument MiningCode1
Mining Legal Arguments in Court DecisionsCode1
Identifying the Human Values behind ArgumentsCode1
IAM: A Comprehensive and Large-Scale Dataset for Integrated Argument Mining TasksCode1
M-Arg: Multimodal Argument Mining Dataset for Political Debates with Audio and TranscriptsCode1
DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language ModelsCode1
ABCD: A Graph Framework to Convert Complex Sentences to a Covering Set of Simple SentencesCode1
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
ELLIS Alicante at CQs-Gen 2025: Winning the critical thinking questions shared task: LLM-based question generation and selection—0
LLMs for Argument Mining: Detection, Extraction, and Relationship Classification of pre-defined Arguments in Online Comments—0
Towards Comprehensive Argument Analysis in Education: Dataset, Tasks, and Method—0
Exploring new Approaches for Information Retrieval through Natural Language Processing—0
Argument Summarization and its Evaluation in the Era of Large Language Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified