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ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation

, , , , , , , , and . Proceedings of Machine Learning Research in 19th Conference on Neurosymbolic Learning and Reasoning, 284, page 1-22. (2025)

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Scaling Usability of ML Analytics with Knowledge Graphs: Exemplified with A Bosch Welding Case., , , , , and . IJCKG, page 54-63. ACM, (2021)Towards Ontology Reshaping for KG Generation with User-in-the-Loop: Applied to Bosch Welding., , , , , and . IJCKG, page 145-150. ACM, (2021)ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation, , , , , , , , and . Proceedings of Machine Learning Research in 19th Conference on Neurosymbolic Learning and Reasoning, 284, page 1-22. (2025)ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation, , , , , , , , and . Proceedings of Machine Learning Research in 19th Conference on Neurosymbolic Learning and Reasoning, 284, page 1-22. (2025)Specializing Versatile Skill Libraries using Local Mixture of Experts., , , , and . CoRL, volume 164 of Proceedings of Machine Learning Research, page 1423-1433. PMLR, (2021)Alleviating Over-Smoothing via Aggregation over Compact Manifolds, , , , and . Advances in Knowledge Discovery and Data Mining : 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part II, volume II of Lecture Notes in Artificial Intelligence, page 390-404. Singapore, Springer, (2024)