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

Showing 201225 of 284 papers

TitleStatusHype
Analyzing the Semantic Types of Claims and Premises in an Online Persuasive Forum0
An Argument-Annotated Corpus of Scientific Publications0
An Empirical Study on Measuring the Similarity of Sentential Arguments with Language Model Domain Adaptation0
A News Editorial Corpus for Mining Argumentation Strategies0
Annotating Claims in the Vaccination Debate0
Annotation of argument structure in Japanese legal documents0
AntCritic: Argument Mining for Free-Form and Visually-Rich Financial Comments0
A Preliminary Study of Disputation Behavior in Online Debating Forum0
Argumentation: Content, Structure, and Relationship with Essay Quality0
Argumentation Quality Assessment: Theory vs. Practice0
Argumentation Synthesis following Rhetorical Strategies0
Argumentative Stance Prediction: An Exploratory Study on Multimodality and Few-Shot Learning0
Argumentative texts and clause types0
Argument Component Classification for Classroom Discussions0
ArgumenText: Searching for Arguments in Heterogeneous Sources0
Argument Harvesting Using Chatbots0
Argument Mining: A Survey0
Argument Mining: Extracting Arguments from Online Dialogue0
Argument Mining for Scholarly Document Processing: Taking Stock and Looking Ahead0
Argument Mining for Understanding Peer Reviews0
Argument Mining on Twitter: A Case Study on the Planned Parenthood Debate0
Argument Mining on Twitter: Arguments, Facts and Sources0
Argument Mining: the Bottleneck of Knowledge and Language Resources0
Argument Mining using BERT and Self-Attention based Embeddings0
Argument Novelty and Validity Assessment via Multitask and Transfer Learning0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06Unverified