Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
NeFL: Nested Model Scaling for Federated Learning with System Heterogeneous Clients
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2308.07761.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T20:24:32.557619Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T09:56:01.599284Z
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 1f81c8f2-4b18-4dfe-b08c-6fbff691885c · inbound
DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices cites this paper.
DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices NeFL: Nested Model Scaling for Federated Learning with System Heterogeneous Clients
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T20:24:32.557619Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8e4c8eb8-4eef-4f29-a0b6-a8653db0f667 · inbound
GeFL: Model-Agnostic Federated Learning with Generative Models cites this paper.
GeFL: Model-Agnostic Federated Learning with Generative Models NeFL: Nested Model Scaling for Federated Learning with System Heterogeneous Clients
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T04:45:42.222834Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 93bb77e6-e434-4e0a-8ed4-3fd149c0cde4 · inbound
Representation-Aligned Multi-Scale Personalization for Federated Learning cites this paper.
Representation-Aligned Multi-Scale Personalization for Federated Learning NeFL: Nested Model Scaling for Federated Learning with System Heterogeneous Clients
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T09:56:01.608344Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.