Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2302.01068.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:22:50.154466Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T16:51:05.426360Z
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 86db1ef7-d72c-485a-9af1-6d8eee3cdd9f · inbound
Cellular Traffic Prediction via Byzantine-robust Asynchronous Federated Learning cites this paper.
Cellular Traffic Prediction via Byzantine-robust Asynchronous Federated Learning FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:22:50.154466Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eaf6078f-f0e1-49d0-ae01-4c4ab43a31b7 · inbound
FLRSP: Privacy-Preserving Federated Learning Using Randomly Selected Model Parameters cites this paper.
FLRSP: Privacy-Preserving Federated Learning Using Randomly Selected Model Parameters FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T16:51:05.429979Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.