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Found 3 papers, 2 papers with code
Boundary Detection and Categorization of Argument Aspects via Supervised Learning
This dataset enables both the supervised learning of boundaries and categorization of argument aspects.
Few-Shot Learning for Argument Aspects of the Nuclear Energy Debate
We approach aspect-based argument mining as a supervised machine learning task to classify arguments into semantically coherent groups referring to the same defined aspect categories.
Few-shot learning for automated content analysis: Efficient coding of arguments and claims in the debate on arms deliveries to Ukraine
In this study, we address these challenges by using a multilingual transformer model in combination with the adapter extension to transformers, and few-shot learning methods.
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