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Found 5 papers, 4 papers with code
Explainable Unsupervised Argument Similarity Rating with Abstract Meaning Representation and Conclusion Generation
When assessing the similarity of arguments, researchers typically use approaches that do not provide interpretable evidence or justifications for their ratings.
Data Augmentation for Improving the Prediction of Validity and Novelty of Argumentative Conclusions
Using only training data retrieved from related datasets by automatically labeling them for validity and novelty, combined with synthetic data, outperforms the baseline by 11. 5 points in F_1-score.
Overview of the 2022 Validity and Novelty Prediction Shared Task
This paper provides an overview of the Argument Validity and Novelty Prediction Shared Task that was organized as part of the 9th Workshop on Argument Mining (ArgMining 2022).
Ranked #1 on
ValNov
on ValNov Subtask A
Architectural Sweet Spots for Modeling Human Label Variation by the Example of Argument Quality: It's Best to Relate Perspectives!
To best represent the interplay of individual and shared perspectives, we consider a continuum of approaches ranging from models that fully aggregate perspectives into a majority label to "share nothing"-architectures in which each annotator is considered in isolation from all other annotators.
Similarity-weighted Construction of Contextualized Commonsense Knowledge Graphs for Knowledge-intense Argumentation Tasks
Arguments often do not make explicit how a conclusion follows from its premises.
