Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.11636.
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 2026-08-12T18:53:06.607779Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T12:20:30.466104Z
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 0e4a8fef-dae7-4b1c-903f-85326b3b08f7 · inbound
F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics cites this paper.
F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities
Reference 78
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T18:53:06.607779Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 475d16e3-15fd-43eb-8af7-01b9c0fc1fa7 · inbound
FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning cites this paper.
FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities
Reference 49
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-11T12:20:30.471483Z
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.