Results 271 to 280 of about 1,930,637 (304)

Mining fine-grained argument elements

, 2014
openaire   +1 more source

Understanding Enthymemes in Argument Maps: Bridging Argument Mining and Logic-based Argumentation

arXiv.org
Argument mining is natural language processing technology aimed at identifying arguments in text. Furthermore, the approach is being developed to identify the premises and claims of those arguments, and to identify the relationships between arguments ...
Jonathan Ben-Naim, Victor David, Anthony Hunter   +2 more
semanticscholar   +3 more sources

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Overview of ImageArg-2023: The First Shared Task in Multimodal Argument Mining

Workshop on Argument Mining, 2023
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.
Zhexiong Liu, Mohamed Elarby, Yang Zhong, Diane J. Litman   +3 more
semanticscholar   +1 more source

Argument Mining with Graph Representation Learning

International Conference on Artificial Intelligence and Law, 2023
Argument Mining (AM) is a unique task in Natural Language Processing (NLP) that targets arguments: a meaningful logical structure in human language. Since the argument plays a significant role in the legal field, the interdisciplinary study of AM on ...
Gechuan Zhang, P. Nulty, David Lillis
semanticscholar   +1 more source

Argument Mining with Modular BERT and Transfer Learning

IEEE International Joint Conference on Neural Network, 2023
We introduce BERT–MINUS, a modular, feature-enriched and transfer learning enabled model for Argument Mining. BERT–MINUS consists of: 1) a joint module which embeds the paragraph text, and 2) a dedicated module, consisting of three customized BERT models,
Umer Mushtaq, Jérémie Cabessa
semanticscholar   +1 more source

Argument Mining

2019
International audience ; This book is an introduction to the linguistic concepts of argumentation relevant for argument mining, an important research and development activity which can be viewed as a highly complex form of information retrieval, requiring high-level natural language processing technology.
Janier, Mathilde, Saint Dizier, Patrick
openaire   +1 more source

Can Large Language Models perform Relation-based Argument Mining?

International Conference on Computational Linguistics
Argument mining (AM) is the process of automatically extracting arguments, their components and/or relations amongst arguments and components from text.
Deniz Gorur, Antonio Rago, Francesca Toni   +2 more
semanticscholar   +1 more source

Large Language Models in Argument Mining: A Survey

arXiv.org
Large Language Models (LLMs) have fundamentally reshaped Argument Mining (AM), shifting it from a pipeline of supervised, task-specific classifiers to a spectrum of prompt-driven, retrieval-augmented, and reasoning-oriented paradigms.
Hao Li, Viktor Schlegel, Yizheng Sun, R. Batista-Navarro, Goran Nenadic   +4 more
semanticscholar   +1 more source

Segmentation of Argumentative Texts by Key Statements for Argument Mining from the Web

Workshop on Argument Mining
Argument mining is the task of identifying the argument structure of a text: claims, premises, support/attack relations, etc. However, determining the complete argument structure can be quite involved, especially for unpolished texts from online forums ...
Ines Zelch, Matthias Hagen, Benno Stein, Johannes Kiesel   +3 more
semanticscholar   +1 more source

LLMs for Argument Mining: Detection, Extraction, and Relationship Classification of pre-defined Arguments in Online Comments

arXiv.org
Automated large-scale analysis of public discussions around contested issues like abortion requires detecting and understanding the use of arguments. While Large Language Models (LLMs) have shown promise in language processing tasks, their performance in
Matteo Guida, Yulia Otmakhova, Eduard H. Hovy, Lea Frermann   +3 more
semanticscholar   +1 more source