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[2602.15553] RUVA: Personalized Transparent On-Device Graph Reasoning
Summary
The paper presents RUVA, a novel architecture for personalized on-device graph reasoning that enhances user control over AI-generated content, addressing privacy and accountability issues in AI systems.
Why It Matters
As AI systems increasingly influence personal data management, RUVA's approach offers a significant shift from opaque 'black box' models to transparent 'glass box' systems. This empowers users to manage their data effectively, ensuring privacy and accountability, which is crucial in today's data-driven landscape.
Key Takeaways
- RUVA enables users to inspect and edit their AI's knowledge.
- The architecture shifts from vector matching to graph reasoning.
- It addresses privacy concerns by allowing precise data redaction.
- Users gain control over their personal data, enhancing accountability.
- The model supports the 'Right to be Forgotten' principle.
Computer Science > Artificial Intelligence arXiv:2602.15553 (cs) [Submitted on 17 Feb 2026] Title:RUVA: Personalized Transparent On-Device Graph Reasoning Authors:Gabriele Conte, Alessio Mattiace, Gianni Carmosino, Potito Aghilar, Giovanni Servedio, Francesco Musicco, Vito Walter Anelli, Tommaso Di Noia, Francesco Maria Donini View a PDF of the paper titled RUVA: Personalized Transparent On-Device Graph Reasoning, by Gabriele Conte and 8 other authors View PDF HTML (experimental) Abstract:The Personal AI landscape is currently dominated by "Black Box" Retrieval-Augmented Generation. While standard vector databases offer statistical matching, they suffer from a fundamental lack of accountability: when an AI hallucinates or retrieves sensitive data, the user cannot inspect the cause nor correct the error. Worse, "deleting" a concept from a vector space is mathematically imprecise, leaving behind probabilistic "ghosts" that violate true privacy. We propose Ruva, the first "Glass Box" architecture designed for Human-in-the-Loop Memory Curation. Ruva grounds Personal AI in a Personal Knowledge Graph, enabling users to inspect what the AI knows and to perform precise redaction of specific facts. By shifting the paradigm from Vector Matching to Graph Reasoning, Ruva ensures the "Right to be Forgotten." Users are the editors of their own lives; Ruva hands them the pen. The project and the demo video are available at this http URL. Subjects: Artificial Intelligence (cs.AI); Computa...
