Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2402.12780.
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 2026-08-15T14:39:14.276427Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T23:06:53.306558Z
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 6d2504b5-dd8c-44ea-b6f5-7f30aa741353 · inbound
Robust Federated Learning under Adversarial Attacks via Loss-Based Client Clustering cites this paper.
Robust Federated Learning under Adversarial Attacks via Loss-Based Client Clustering Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T23:06:53.308557Z
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 081bc29c-0835-4073-b5ad-8733fbe7e5d5 · inbound
FedGreed: A Byzantine-Robust Loss-Based Aggregation Method for Federated Learning cites this paper.
FedGreed: A Byzantine-Robust Loss-Based Aggregation Method for Federated Learning Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T16:41:11.337041Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f31d589e-462b-494e-935f-b28a49059d6f · inbound
Theoretical Foundations of Communication-Efficient, Robust, and Practical Distributed and Federated Optimization cites this paper.
Theoretical Foundations of Communication-Efficient, Robust, and Practical Distributed and Federated Optimization Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:39:14.276427Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.