Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
How To Backdoor Federated Learning
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1807.00459.
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 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:27:05.594480Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T11:29:50.192546Z
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 e9e9abc4-8875-4e6a-9d5d-f8c3b60c6e51 · inbound
PPFL-RDSN: Privacy-Preserving Federated Learning-based Residual Dense Spatial Networks for Encrypted Lossy Image Reconstruction cites this paper.
PPFL-RDSN: Privacy-Preserving Federated Learning-based Residual Dense Spatial Networks for Encrypted Lossy Image Reconstruction How To Backdoor Federated Learning
Reference 63
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:27:05.594480Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf1a69f6-d768-48af-94a6-a67885e4cf4b · inbound
HADES: Privacy-Preserving Federated Learning via Selective Feature Encryption and Hybrid Model Fusion cites this paper.
HADES: Privacy-Preserving Federated Learning via Selective Feature Encryption and Hybrid Model Fusion How To Backdoor Federated Learning
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T11:29:50.194086Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c882e407-5bb2-4504-8604-aa79a9b02349 · 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 How To Backdoor Federated Learning
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T22:47:13.609330Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation adbbacdc-11bb-4b1b-81bb-79c1dbc0f3a9 · 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 How To Backdoor Federated Learning
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T01:42:10.035450Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.