An LLM-guided platform for multi-granular collection and management of data provenance
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- 5.Jacovi A, Marasović A, Miller T, Goldberg Y. Formalizing trust in artificial intelligence: Prerequisites, causes and goals of human trust in ai. In: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. FAccT ’21, pp. 624–635. Association for Computing Machinery, New York, NY, USA 2021. https://doi.org/10.1145/3442188.3445923
- 11.Namaki MH, Floratou A, Psallidas F, Krishnan S, Agrawal A, Wu Y, et al. Vamsa: Automated provenance tracking in data science scripts. In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. KDD ’20, pp. 1542–1551. Association for Computing Machinery, New York, NY, USA 2020. https://doi.org/10.1145/3394486.3403205
- 20.
Peeking inside the black-box: a survey on explainable artificial intelligence (XAI)
Adadi, A; Berrada, M. IEEE Access Vol. 6, .- Times cited 2 on ProQuest