Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2410.15267.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T21:44:59.178089Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-15T23:21:42.749198Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 40544e37-6abf-4999-bc1b-13c584e31eb4 · inbound
(De)-Indexing and the Right to be Forgotten cites this paper.
(De)-Indexing and the Right to be Forgotten When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:44:59.178089Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 03d47b21-c76b-49d6-921c-39089b70d8d9 · inbound
SoK: Machine Unlearning for Large Language Models cites this paper.
SoK: Machine Unlearning for Large Language Models When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:58:51.297979Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation daf20d88-fa05-4d3b-a8a3-06ff188b4a43 · inbound
Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs cites this paper.
Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:15:35.857559Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a57f91a6-aca5-445e-918b-d640465cbd52 · inbound
A Survey on Generative Model Unlearning: Fundamentals, Taxonomy, Evaluation, and Future Direction cites this paper.
A Survey on Generative Model Unlearning: Fundamentals, Taxonomy, Evaluation, and Future Direction When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?
Reference 229
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:54:40.397808Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1bff5fe6-23a5-4098-9444-52231e88c75c · inbound
A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems cites this paper.
A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?
Reference 100
- Resolution
- verified exact
- arxiv_id, observed 2026-07-17T02:21:27.470066Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.