mlsanityData to 7 Oct 2026

RUVA: Personalized Transparent On-Device Graph Reasoning

arXiv 2602.15553 ↗First posted 17 Feb 2026cs.AI cs.CLcited by 0

On the map: Retrieval-augmented generation → Privacy and security of RAG

Abstract (arXiv)

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 http://sisinf00.poliba.it/ruva/.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Privacy and security of RAG, one of 15 directions in Retrieval-augmented generation. Builds on 16 of its 28 references that are in the map. First posted on arXiv 17 Feb 2026.

Builds on

16 of 28 references.

References · 16

  1. 2024The Llama 3 Herd of Modelscited by 14,192
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2025Qwen3 Technical Reportcited by 8,195
  4. 2025Gemma 3 Technical Reportcited by 1,686
  5. 2024From Local to Global: A Graph RAG Approach to Query-Focused Summarizationcited by 1,411
  6. 2025gpt-oss-120b & gpt-oss-20b Model Cardcited by 1,258
  7. 2023An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuningcited by 622
  8. 2023Prometheus: Inducing Fine-grained Evaluation Capability in Language Modelscited by 558
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  11. 2025The Widespread Adoption of Large Language Model-Assisted Writing Across Societycited by 50
  12. 2024When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?cited by 20
4 more
  1. 2025LLaMAs Have Feelings Too: Unveiling Sentiment and Emotion Representations in LLaMA Models Through Probingcited by 14
  2. 2023An Ecosystem for Personal Knowledge Graphs: A Survey and Research Roadmapcited by 11
  3. 2024Scalable Cloud-Native Pipeline for Efficient 3D Model Reconstruction from Monocular Smartphone Imagescited by 2
  4. 2025Training-Free, Identity-Preserving Image Editing for Fashion Pose Alignment and Normalizationcited by 2

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  2. 2026Opal: Private Memory for Personal AI
  3. 2026SmartRAG: Native Graph-Based RAG for Mobile Device
  4. 2026HGP:An on-device personalized agent memory via hybrid graph storage
  5. 2026PrivGemo: Privacy-Preserving Dual-Tower Graph Retrieval for Empowering LLM Reasoning with Memory Augmentation
  6. 2026PersonalAI 2.0: Enhancing knowledge graph traversal/retrieval with planning mechanism for Personalized LLM Agents
  7. 2026Kernel-Managed Shared Memory for System-Wide Personalization
  8. 2025Training-Free Personalization via Retrieval and Reasoning on Fingerprints