Paper Citation Record · LEDGER

On the Detectability of Active Gradient Inversion Attacks in Federated Learning

As of 10 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2511.10502.

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

pith.paper-citation-record.v1
2511.10502 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T22:28:55.469518Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

verified exact0
verified fuzzy0
unresolved35
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation da6079db-30c5-4d48-8f23-8211f458764d · outbound

This paper cites When machine learning meets privacy: A survey and outlook,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning When machine learning meets privacy: A survey and outlook,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:49.963529Z

Source-reported events for the cited work

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Observation 6baf34ea-b237-4ac1-9a5d-99b7e5e3f89c · outbound

This paper cites Communication-efficient learning of deep networks from decentral- ized data,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Communication-efficient learning of deep networks from decentral- ized data,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:50.059327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d68cdbf-5619-4b34-99a5-a7fc8236f5bb · outbound

This paper cites Decentralised Learning in Federated Deployment Environments: A System-Level Survey,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Decentralised Learning in Federated Deployment Environments: A System-Level Survey,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:50.288367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52e64af3-0afd-43bb-9d26-5382059e7514 · outbound

This paper cites Sok: Gradient inversion attacks in federated learning,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Sok: Gradient inversion attacks in federated learning,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:50.545390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10053233-8bef-48ed-9beb-b6da43dfbbb3 · outbound

This paper cites Sok: Gradient leakage in federated learning,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Sok: Gradient leakage in federated learning,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:50.719372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation feeb1175-bbe0-4a2d-88df-dc434744e20d · outbound

This paper cites Hiding in plain sight: Disguising data stealing attacks in federated learning,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Hiding in plain sight: Disguising data stealing attacks in federated learning,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:50.861810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf9e38d9-032a-4949-8e64-21e37890ad7f · outbound

This paper cites Hear No Evil: Detecting Gradient Leakage by Malicious Servers in Federated Learning.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Hear No Evil: Detecting Gradient Leakage by Malicious Servers in Federated Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:50.979969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36c076b9-6048-44c2-a890-f1f33c5f996e · outbound

This paper cites Robbing the fed: Directly obtaining private data in federated learning with modified models.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Robbing the fed: Directly obtaining private data in federated learning with modified models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:51.138017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fa3e384-c46b-4253-b58d-9597a96d4856 · outbound

This paper cites Loki: Large-scale data reconstruction attack against federated learning through model manipulation,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Loki: Large-scale data reconstruction attack against federated learning through model manipulation,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:51.365911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb5da412-a9a1-4698-a599-a35f2119e59a · outbound

This paper cites Fishing for user data in large-batch federated learning via gradient magnification,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Fishing for user data in large-batch federated learning via gradient magnification,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:51.622657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5074a24-197f-48e8-b4a7-d0eb15e0f958 · outbound

This paper cites When the curious abandon honesty: Fed- erated learning is not private,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning When the curious abandon honesty: Fed- erated learning is not private,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:51.772318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7485c15-e0d7-4bfb-a05f-428f778faa3d · outbound

This paper cites Reconstructing individual data points in federated learning hardened with differential privacy and secure aggregation,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Reconstructing individual data points in federated learning hardened with differential privacy and secure aggregation,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:51.932317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a40bbfcc-981d-4008-8ba3-267ab9b79924 · outbound

This paper cites Maximum knowledge orthogonality reconstruction with gradients in federated learning,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Maximum knowledge orthogonality reconstruction with gradients in federated learning,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:52.104615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6808906-bfd1-4848-9217-ee247c009c49 · outbound

This paper cites Scale-mia: A scalable model inversion attack against secure federated learning via latent space reconstruction,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Scale-mia: A scalable model inversion attack against secure federated learning via latent space reconstruction,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:52.212507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e4f813d-52dd-4d75-8927-3f87654a3573 · outbound

This paper cites Geminio: Language-guided gradient inversion attacks in federated learning,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Geminio: Language-guided gradient inversion attacks in federated learning,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:52.378362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b456e3cc-6e35-44f5-973d-be05ed0d5e8c · outbound

This paper cites Deep leakage from gradients,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Deep leakage from gradients,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:52.500347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c260ebc1-df14-4b8a-9658-9bb1fc1a704e · outbound

This paper cites Inverting gradients - how easy is it to break privacy in federated learning?.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Inverting gradients - how easy is it to break privacy in federated learning?

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:52.618469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9d1fbf8-886e-472f-9d26-99050d84a72f · outbound

This paper cites Flower: A Friendly Federated Learning Research Framework.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Flower: A Friendly Federated Learning Research Framework

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:52.758453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bef96c45-6109-496d-ad8c-0ff9a4446836 · outbound

This paper cites Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:52.926280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 135f20f7-7179-4f9f-9c0b-46a3b12f3458 · outbound

This paper cites Learning multiple layers of features from tiny images,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Learning multiple layers of features from tiny images,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:53.054400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e981d35e-ea91-44f8-adb3-fee67f24ef59 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Imagenet: A large-scale hierarchical image database,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:53.197048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d4e30bc-c7e1-455a-a3a6-9518d4203740 · outbound

This paper cites The mnist database of handwritten digit images for machine learning research [best of the web],.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning The mnist database of handwritten digit images for machine learning research [best of the web],

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:53.308937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cdc2419-056f-42ac-87de-5dbb960d6007 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:53.418826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff4a2be9-a288-4b95-88c0-e91fcb6f56a2 · outbound

This paper cites Deep residual learning for image recognition,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Deep residual learning for image recognition,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:53.480735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d04d501-4447-4b05-a791-f9c0b63551ca · outbound

This paper cites Gradient-based learning applied to document recognition,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Gradient-based learning applied to document recognition,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:53.641085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0f6e919-0e21-41eb-ba86-6a64c939e432 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:53.800898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f67da76c-3d66-402c-9e90-8de805f5d41f · outbound

This paper cites The resource problem of using linear layer leak- age attack in federated learning,.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning The resource problem of using linear layer leak- age attack in federated learning,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:53.968777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dfb6da5-d7b6-4c55-97e9-ee00f0d747af · outbound

This paper cites an unresolved cited work.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:54.134730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06e83374-30a9-48f0-a7a9-6775dc8fcac7 · outbound

This paper cites an unresolved cited work.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Unresolved cited work

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:54.311488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6a82e72-208c-4708-9daf-635709595434 · outbound

This paper cites an unresolved cited work.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Unresolved cited work

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:54.472899Z

Source-reported events for the cited work

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Observation b7e1d709-cfde-438b-a637-3aa42c8eecb5 · outbound

This paper cites an unresolved cited work.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Unresolved cited work

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:54.805316Z

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Observation c4ce71cd-1a04-4ed7-ad1c-91ffcfb1ae39 · outbound

This paper cites an unresolved cited work.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:54.917375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62081286-2eb0-48f0-ae98-7905c3b5fb03 · outbound

This paper cites an unresolved cited work.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Unresolved cited work

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:55.029181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39eb687d-eb68-4443-8182-bd26c6dade6f · outbound

This paper cites an unresolved cited work.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Unresolved cited work

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:55.195136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70d881db-77de-4b7d-8f9d-2a4b99116d42 · outbound

This paper cites an unresolved cited work.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning Unresolved cited work

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:55.359373Z

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Unavailable: canonical work link unavailable.

Observation bbe31d1c-b025-46b6-bcea-ffc05c481cda · outbound

This paper cites All experiments simulate an IID data distribution.

On the Detectability of Active Gradient Inversion Attacks in Federated Learning All experiments simulate an IID data distribution

Reference 37

Resolution: malformed identifier; no resolver link, observed 2026-08-03T22:28:55.469518Z

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Pith citing papers

No inbound Pith citation observations are available.