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 101–125 of 284 papers

TitleStatusHype
Argumentation: Content, Structure, and Relationship with Essay Quality—0
Defeasible AceRules: A Prototype—0
Explainable Topic-Enhanced Argument Mining from Heterogeneous Sources—0
A Hybrid Intelligence Method for Argument Mining—0
Argument Novelty and Validity Assessment via Multitask and Transfer Learning—0
Discourse as a Function of Event: Profiling Discourse Structure in News Articles around the Main Event—0
Argument Relation Classification Using a Joint Inference Model—0
Annotation of argument structure in Japanese legal documents—0
ECHR: Legal Corpus for Argument Mining—0
Argument Summarization and its Evaluation in the Era of Large Language Models—0
Efficient argument classification with compact language models and ChatGPT-4 refinements—0
ELLIS Alicante at CQs-Gen 2025: Winning the critical thinking questions shared task: LLM-based question generation and selection—0
End-to-End Argumentation Mining in Student Essays—0
A Generative Marker Enhanced End-to-End Framework for Argument Mining—0
End-to-End Argument Mining as Biaffine Dependency Parsing—0
End-to-End Argument Mining for Discussion Threads Based on Parallel Constrained Pointer Architecture—0
Investigating Logic Tensor Networks for Neural-Symbolic Argument Mining—0
Enhancing Investment Opinion Ranking through Argument-Based Sentiment Analysis—0
Advances in Debating Technologies: Building AI That Can Debate Humans—0
A Corpus of Argument Networks: Using Graph Properties to Analyse Divisive Issues—0
ESCRITO - An NLP-Enhanced Educational Scoring Toolkit—0
Evidence Type Classification in Randomized Controlled Trials—0
Evidence Types, Credibility Factors, and Patterns or Soft Rules for Weighing Conflicting Evidence: Argument Mining in the Context of Legal Rules Governing Evidence Assessment—0
Expert Stance Graphs for Computational Argumentation—0
Exploring new Approaches for Information Retrieval through Natural Language Processing—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified