Paper Citation Record · LEDGER

Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2202.00580.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2202.00580 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:31:27.332892Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T04:39:35.030793Z

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 276c7e10-e486-43f3-b999-a0e9fe32c6f8 · inbound

Hidden Data Privacy Breaches in Federated Learning cites this paper.

Hidden Data Privacy Breaches in Federated Learning Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T11:26:17.107366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b329722-6385-4f64-9a6b-645d0594cf5e · inbound

Gradient Inversion Attack on Graph Neural Networks cites this paper.

Gradient Inversion Attack on Graph Neural Networks Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-12T10:17:09.994808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72fc3d53-8dcf-4938-aa96-129952128bb8 · inbound

CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling cites this paper.

CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T14:05:45.510473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db54f403-5f5b-4dfd-bf5e-28f6b71f21ad · inbound

ReCIT: Reconstructing Full Private Data from Gradient in Parameter-Efficient Fine-Tuning of Large Language Models cites this paper.

ReCIT: Reconstructing Full Private Data from Gradient in Parameter-Efficient Fine-Tuning of Large Language Models Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T05:31:27.332892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a72c9911-f588-4ec4-97d8-d55fcc1b39fa · inbound

FLRSP: Privacy-Preserving Federated Learning Using Randomly Selected Model Parameters cites this paper.

FLRSP: Privacy-Preserving Federated Learning Using Randomly Selected Model Parameters Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:51:05.423372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 31ec78ff-038b-4d9a-915f-f05ca0e0aef3 · 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 Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-07-04T04:39:35.032288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.