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Original version
Antoniou, G.; Batsakis, S.: Defeasible Reasoning with Large Language Models - Initial Experiments and Future Directions. In: Vanthienen, Jan; Kliegr, Tomáš; Fodor, Paul; Lanti, Davide; Arndt, Dörthe; Kostylev, Egor V.; Mitsikas, Theodoros; Soylu, Ahmet (Eds.): RuleML+RR-Companion 2023: RuleML+RR Challenge and Doctoral Consortium 2023 : proceedings of the 17th International Rule Challenge and 7th Doctoral Consortium @ RuleML+RR 2023 co-located with 19th Reasoning Web Summer School (RW 2023) and 15th DecisionCAMP 2023 as part of Declarative AI 2023. Aachen, Germany : RWTH Aachen, 2023 (CEUR workshop proceedings ; 3485), 7687.
Repository version
To cite the version in the repository, please use this identifier:
https://doi.org/10.15488/16489
Files in this item
| Abstract: | |
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As Large Language Models gain prominence in the AI landscape, it is essential to understand their capabilities and limitations, among others in terms of reasoning. This paper is a first step towards understanding the capabilities in terms of defeasible rule-based reasoning. It presents results of initial experiments and discussed future research directions.
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| License of this version: | CC BY 4.0 Unported - https://creativecommons.org/licenses/by/4.0 |
| Publication type: | BookPart |
| Publishing status: | publishedVersion |
| Publication date: | 2023 |
| Keywords english: | Defeasible Reasoning, Large Language Models, Non-monotonic Reasoning |
| DDC: | 004 | Informatik |
| Controlled keywords(GND): | Konferenzschrift |
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