DOTRAG: Retrieval-Time Reasoning Along Paths

2026-05-20T08:52:17Z37b8c3f385e3e6e6129410ffc209e5d901bb9093e2ec5b09bf6d7368a94bf633
ALDENGraphRAGPIIRAGactive-learningadversarial-queriesauditabilitycode-releasedata-exfiltrationdistribution-estimationhealthcareknowledge-graphmodel-misusemulti-hop-retrievalprivacyprovenancequery-conditioningretrieval-augmented-generationwearable-data

What happened

This feed contains multiple papers on Retrieval-Augmented Generation (RAG) and GraphRAG advances and one security-focused paper (ALDEN) that materially raises privacy risks. ALDEN demonstrates a practical, high‑efficiency private data extraction attack against RAG systems by combining active learning to diversify malicious queries with a decay-based dynamic algorithm to estimate topic/distribution of the underlying knowledge base — substantially outperforming prior extraction methods. Related papers (DotRAG, STAR, ClusterRAG, Agentic GraphRAG, ClinQueryAgent, WAG, etc.) improve query‑condition

Why it matters

A reviewed impact interpretation has not been published for this record.

Evidence and limitations

Source ID
arxiv_cs_ir
Record identifier
37b8c3f385e3e6e6129410ffc209e5d901bb9093e2ec5b09bf6d7368a94bf633
Enrichment time
2026-05-20T08:52:17Z
AI-assisted enrichment
Yes

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