ArgRAG: Explainable retrieval augmented generation using quantitative bipolar argumentation

Zhu, Yuqicheng, Potyka, Nico, Hernández, Daniel, He, Yuan, Ding, Zifeng, Xiong, Bo, Zhou, Dongzhuoran, Kharlamov, Evgeny and Staab, Steffen 2025. ArgRAG: Explainable retrieval augmented generation using quantitative bipolar argumentation. Presented at: 19th International Conference on Neurosymbolic Learning and Reasoning (NeSy), USA, 8 - 10 September 2025. Proceedings of Machine Learning Research. , vol.284 Item availability restricted.

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Item Type:	Conference or Workshop Item (Paper)
Status:	In Press
Schools:	Schools > Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Date of First Compliant Deposit:	23 September 2025
Date of Acceptance:	20 April 2025
Last Modified:	23 Sep 2025 11:15
URI:	https://orca.cardiff.ac.uk/id/eprint/181190

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