Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2110.13057.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T22:44:11.391693Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T04:39:35.019824Z
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 b34d7c93-3f9d-4df6-9fb0-02807f1d3c3e · inbound
A Survey of Secure Semantic Communications cites this paper.
A Survey of Secure Semantic Communications Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models
Reference 78
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:44:11.391693Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a77a8abc-865a-45fb-a430-7db2f5062bb2 · inbound
CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling cites this paper.
CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T14:05:45.506545Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd5b3fd7-6f09-4a33-b7a5-de293c771d5f · inbound
Federated Learning for Anomaly Detection in Energy Consumption Data: Assessing the Vulnerability to Adversarial Attacks cites this paper.
Federated Learning for Anomaly Detection in Energy Consumption Data: Assessing the Vulnerability to Adversarial Attacks Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T20:30:46.357741Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 569fbc1a-4eb9-4374-9a70-e2bbcb433954 · inbound
From Efficiency to Leakage -- Privacy Backdoor in Federated Language Model Fine-Tuning cites this paper.
From Efficiency to Leakage -- Privacy Backdoor in Federated Language Model Fine-Tuning Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T04:39:35.021336Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 50427c0e-df0f-4ea4-90a3-fcef341eda1e · inbound
Privacy Leakage in Federated Learning in Radiology Reports: A Comparative Evaluation of Tokenizer-Driven Privacy Risks cites this paper.
Privacy Leakage in Federated Learning in Radiology Reports: A Comparative Evaluation of Tokenizer-Driven Privacy Risks Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T02:54:03.989583Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.