Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2205.10110.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:39:29.665646Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T08:32:44.124434Z
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 ad943a29-121e-41c9-a5cb-b8f4ad3fab5b · inbound
Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels cites this paper.
Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T08:32:44.128233Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1ee43c68-fdc0-445a-97b4-f653c0080043 · inbound
Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels cites this paper.
Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T05:30:16.327183Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6bb88e30-86a0-48a3-8193-b552535ebeeb · inbound
FNBench: Benchmarking Robust Federated Learning against Noisy Labels cites this paper.
FNBench: Benchmarking Robust Federated Learning against Noisy Labels FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels
Reference 101
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:39:29.665646Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cb0d244a-e77f-4725-883e-50173590ea53 · inbound
FedGSCA: Medical Federated Learning with Global Sample Selector and Client Adaptive Adjuster under Label Noise cites this paper.
FedGSCA: Medical Federated Learning with Global Sample Selector and Client Adaptive Adjuster under Label Noise FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:58:20.517112Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 41d1caeb-fa30-4b18-8df1-982df52df3f0 · inbound
SplitFed-CL: A Split Federated Co-Learning Framework for Medical Image Segmentation with Inaccurate Labels cites this paper.
SplitFed-CL: A Split Federated Co-Learning Framework for Medical Image Segmentation with Inaccurate Labels FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T01:22:01.921120Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.