Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2503.07505.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:57:00.420534Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T23:49:15.075461Z
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 dcce3753-ec04-4409-9ead-3e1e6fd5d5c7 · inbound
Generalization Error Analysis for Attack-Free and Byzantine-Resilient Decentralized Learning with Data Heterogeneity cites this paper.
Generalization Error Analysis for Attack-Free and Byzantine-Resilient Decentralized Learning with Data Heterogeneity From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:57:00.420534Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2e0e0b06-7209-4e81-a62f-e20050e41a2a · inbound
Federated Learning: An approach with Hybrid Homomorphic Encryption cites this paper.
Federated Learning: An approach with Hybrid Homomorphic Encryption From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T11:02:17.477463Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 95465005-03ff-4abb-a418-65dcca8dabaa · inbound
Decision-Focused Federated Learning Under Heterogeneous Objectives and Constraints cites this paper.
Decision-Focused Federated Learning Under Heterogeneous Objectives and Constraints From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:36:04.582974Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c3b99442-19ef-45d0-8c15-c51a3db2e636 · inbound
Decision-Focused Federated Learning Under Heterogeneous Objectives and Constraints cites this paper.
Decision-Focused Federated Learning Under Heterogeneous Objectives and Constraints From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T23:49:15.078546Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.