Ruprecht-Karls-Universität Heidelberg
Bilder vom Neuenheimer Feld, Heidelberg und der Universität Heidelberg
Siegel der Uni Heidelberg

Title: Explanatory Argument Similarity Measurements with Abstract Meaning Representation and Generated Conclusions

Speaker: Juri Opitz (ICL)


In this talk, we will discuss some recent insights into measuring argument similarity. In contrast to most other works, we are interested in making the similiarity computation more transparent and explainable. In particular, we investigate two hypotheses: First, that representing arguments with abstract meaning representation (AMR) and measuring distance between arguments with AMR metrics improves argument similarity assessment. And second, that similar arguments may lead to similar conclusions. We examine these hypotheses by viewing argument similarity through the lens of conclusions that we generate using a pre-trained language model. Our experiments strongly confirm hypotheses one and provide weak evidence for hypothesis two. We also note that the second hypothesis puts the spotlight on a pressing issue: what's a (good) conclusion?
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