Argument Mining
85 papers with code • 1 benchmarks • 6 datasets
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
Benchmarks
These leaderboards are used to track progress in Argument Mining
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Subtasks
Latest papers
DMON: A Simple yet Effective Approach for Argument Structure Learning
vrcmf/dmon
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Argument structure learning~(ASL) entails predicting relations between arguments.
WIBA: What Is Being Argued? A Comprehensive Approach to Argument Mining
Armaniii/WIBA
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First, we develop and release an Argument Detection model that can classify a piece of text as an argument with an F1 score between 79% and 86% on three different benchmark datasets.
Exploring Key Point Analysis with Pairwise Generation and Graph Partitioning
alibaba-nlp/key-point-analysis
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Our objective is to train a generative model that can simultaneously provide a score indicating the presence of shared key point between a pair of arguments and generate the shared key point.
A School Student Essay Corpus for Analyzing Interactions of Argumentative Structure and Quality
When combined with automatic essay scoring, interactions of the argumentative structure and quality scores can be exploited for comprehensive writing support.
TACO -- Twitter Arguments from COnversations
Twitter has emerged as a global hub for engaging in online conversations and as a research corpus for various disciplines that have recognized the significance of its user-generated content.
End-to-End Argument Mining over Varying Rhetorical Structures
Rhetorical Structure Theory implies no single discourse interpretation of a text, and the limitations of RST parsers further exacerbate inconsistent parsing of similar structures.
Exploring the Potential of Large Language Models in Computational Argumentation
As large language models have demonstrated strong abilities in understanding context and generating natural language, it is worthwhile to evaluate the performance of LLMs on various computational argumentation tasks.
Data and models for stance and premise detection in COVID-19 tweets: insights from the Social Media Mining for Health (SMM4H) 2022 shared task
veranchos/argmining_tweets
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The COVID-19 pandemic has sparked numerous discussions on social media platforms, with users sharing their views on topics such as mask-wearing and vaccination.
Overview of ImageArg-2023: The First Shared Task in Multimodal Argument Mining
This paper presents an overview of the ImageArg shared task, the first multimodal Argument Mining shared task co-located with the 10th Workshop on Argument Mining at EMNLP 2023.
TILFA: A Unified Framework for Text, Image, and Layout Fusion in Argument Mining
A main goal of Argument Mining (AM) is to analyze an author's stance.
