ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation.

Yuqicheng Zhu, Nico Potyka, Daniel Hernndez, Yuan He, Zifeng Ding, Bo Xiong, Dongzhuoran Zhou, Evgeny Kharlamov, Steffen Staab

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