Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
When the Curious Abandon Honesty: Federated Learning Is Not Private
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2112.02918.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:27:03.558621Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T09:25:40.732646Z
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 fd87932e-9373-4402-b274-6eab6afddb98 · inbound
Gradient Inversion Attack on Graph Neural Networks cites this paper.
Gradient Inversion Attack on Graph Neural Networks When the Curious Abandon Honesty: Federated Learning Is Not Private
Reference 2016
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T10:17:09.856923Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 323309c4-763e-4a6c-901e-0d10f7599bd0 · inbound
Securing Genomic Data Against Inference Attacks in Federated Learning Environments cites this paper.
Securing Genomic Data Against Inference Attacks in Federated Learning Environments When the Curious Abandon Honesty: Federated Learning Is Not Private
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:27:03.558621Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 096c1305-e54e-4a28-a9d1-14bdbd60ab02 · inbound
Probing Memorization of Tabular In-Context Learning cites this paper.
Probing Memorization of Tabular In-Context Learning When the Curious Abandon Honesty: Federated Learning Is Not Private
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T09:25:40.734546Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 161d3a1b-47cd-4fce-9666-c38ad101572a · inbound
TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement cites this paper.
TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement When the Curious Abandon Honesty: Federated Learning Is Not Private
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T22:47:13.934255Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 92b146f7-4dfc-4b75-afee-7f515f591934 · inbound
TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement cites this paper.
TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement When the Curious Abandon Honesty: Federated Learning Is Not Private
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T01:42:10.522334Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.