Paper Citation Record · LEDGER

Upcycling Noise for Federated Unlearning

As of 16 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2412.05529.

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

pith.paper-citation-record.v1
2412.05529 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:44:14.990803Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

39 of 39 outbound references displayed

verified exact1
verified fuzzy15
unresolved23
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ca365848-f232-4643-8249-6897d7ee00f9 · outbound

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

Upcycling Noise for Federated Unlearning Communication-efficient learning of deep networks from decentralized data,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.768654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b071f57-d5c8-4a37-b403-d74ff90e048c · outbound

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

Upcycling Noise for Federated Unlearning Inverting gradients-how easy is it to break privacy in federated learning?

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.698419Z

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 fa082aa5-b40a-4ed7-b1e5-adfa4e7dd0f3 · outbound

This paper cites Feature inference attack on model predictions in vertical federated learning,.

Upcycling Noise for Federated Unlearning Feature inference attack on model predictions in vertical federated learning,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.679686Z

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 43776a61-a3db-446e-bfab-2fb0a4573c21 · outbound

This paper cites Auditing privacy defenses in federated learning via generative gradient leakage,.

Upcycling Noise for Federated Unlearning Auditing privacy defenses in federated learning via generative gradient leakage,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.786798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3feea60a-bd28-41f8-aa06-959f9a8d91ea · outbound

This paper cites Differentially Private Federated Learning: A Client Level Perspective.

Upcycling Noise for Federated Unlearning Differentially Private Federated Learning: A Client Level Perspective

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.792543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdd2d18d-b990-4ac1-af65-dcf554057adc · outbound

This paper cites Federated learning with differential privacy: Algorithms and performance analysis,.

Upcycling Noise for Federated Unlearning Federated learning with differential privacy: Algorithms and performance analysis,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.801216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94ec30c2-8545-4e82-bd68-5e73d444de84 · outbound

This paper cites Regulation (eu) 2016/679 of the european parliament and of the council,.

Upcycling Noise for Federated Unlearning Regulation (eu) 2016/679 of the european parliament and of the council,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.807920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67405c83-6542-44ff-814f-56df01380f12 · outbound

This paper cites The eu general data protection regu- lation (gdpr),.

Upcycling Noise for Federated Unlearning The eu general data protection regu- lation (gdpr),

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.813990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2cc29b6-2f3b-4d83-8d9e-80978f786f7c · outbound

This paper cites Federaser: Enabling efficient client-level data removal from federated learning models,.

Upcycling Noise for Federated Unlearning Federaser: Enabling efficient client-level data removal from federated learning models,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.820247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1969a9b-43c1-4865-9c8c-1f7ad4e73a95 · outbound

This paper cites Federated unlearning with momentum degradation,.

Upcycling Noise for Federated Unlearning Federated unlearning with momentum degradation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.602672Z

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 1e37bb5d-b343-4767-bef5-c6e1b9d811be · outbound

This paper cites Federated unlearning for on-device recommendation,.

Upcycling Noise for Federated Unlearning Federated unlearning for on-device recommendation,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.583855Z

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 80899c1a-ae06-437a-9a26-ea55e9b4a9fb · outbound

This paper cites The right to be forgotten in federated learning: An efficient realization with rapid retraining,.

Upcycling Noise for Federated Unlearning The right to be forgotten in federated learning: An efficient realization with rapid retraining,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.836416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7beb68d1-6086-4543-9d81-cc6590b1b662 · outbound

This paper cites Federated Unlearning: How to Efficiently Erase a Client in FL?.

Upcycling Noise for Federated Unlearning Federated Unlearning: How to Efficiently Erase a Client in FL?

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.845803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 795e2b57-5d38-4d52-8e19-d51238d5eed2 · outbound

This paper cites Fedrecover: Recovering from poisoning attacks in federated learning using historical information,.

Upcycling Noise for Federated Unlearning Fedrecover: Recovering from poisoning attacks in federated learning using historical information,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.553383Z

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 67e8da69-616f-4194-86b3-3590720f980f · outbound

This paper cites Incentive mechanism design for federated learning and unlearning,.

Upcycling Noise for Federated Unlearning Incentive mechanism design for federated learning and unlearning,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.858195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebea0d29-39f8-4186-a3b6-fd1c963c60d5 · outbound

This paper cites Federated Unlearning with Knowledge Distillation.

Upcycling Noise for Federated Unlearning Federated Unlearning with Knowledge Distillation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.863494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55927ed6-e838-4f94-8e98-fdf7ab2974da · outbound

This paper cites Federated unlearning via class- discriminative pruning,.

Upcycling Noise for Federated Unlearning Federated unlearning via class- discriminative pruning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.522459Z

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 0f8e2733-d62c-428c-89ce-0d2a180e6f51 · outbound

This paper cites Fedme 2: Memory evaluation & erase promoting federated unlearning in dtmn,.

Upcycling Noise for Federated Unlearning Fedme 2: Memory evaluation & erase promoting federated unlearning in dtmn,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.504119Z

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 b69605e7-7626-40d5-9a37-7692f7fceead · outbound

This paper cites Fedrecovery: Dif- ferentially private machine unlearning for federated learning frameworks,.

Upcycling Noise for Federated Unlearning Fedrecovery: Dif- ferentially private machine unlearning for federated learning frameworks,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.486101Z

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 2a5c48ab-40a0-4dff-a86c-1e23cf042584 · outbound

This paper cites Get Rid Of Your Trail: Remotely Erasing Backdoors in Federated Learning.

Upcycling Noise for Federated Unlearning Get Rid Of Your Trail: Remotely Erasing Backdoors in Federated Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.888169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 817bbde7-dbc1-4cf5-a8bb-94efc7e55ac6 · outbound

This paper cites Bayesian variational federated learning and unlearning in decentralized networks,.

Upcycling Noise for Federated Unlearning Bayesian variational federated learning and unlearning in decentralized networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.465569Z

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 318cdc6e-e5b0-4f26-a7bd-e6c894882ab3 · outbound

This paper cites On the limited memory bfgs method for large scale optimization,.

Upcycling Noise for Federated Unlearning On the limited memory bfgs method for large scale optimization,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.899258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30fa1a94-181a-4878-8950-7948184e4e06 · outbound

This paper cites Learning Differentially Private Recurrent Language Models.

Upcycling Noise for Federated Unlearning Learning Differentially Private Recurrent Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.904405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f5dc7b5-3805-4b9b-8c9a-eb06105f6cce · outbound

This paper cites Ldp-fed: Federated learning with local differential privacy,.

Upcycling Noise for Federated Unlearning Ldp-fed: Federated learning with local differential privacy,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.909343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72fa6660-a668-421a-a030-7db6c9488dc0 · outbound

This paper cites Shuffled model of differential privacy in federated learning,.

Upcycling Noise for Federated Unlearning Shuffled model of differential privacy in federated learning,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.420552Z

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 b2d808f8-ca36-463d-a11f-b9090b779540 · outbound

This paper cites Federated learning with differential privacy for resilient vehicular cyber physical systems,.

Upcycling Noise for Federated Unlearning Federated learning with differential privacy for resilient vehicular cyber physical systems,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.397716Z

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 0938c75e-69ef-4b1a-8b5e-f6cd9261174e · outbound

This paper cites Local differential privacy-based federated learning for internet of things,.

Upcycling Noise for Federated Unlearning Local differential privacy-based federated learning for internet of things,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.925520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d12f95aa-e51a-4a6a-956b-49bfafb0751a · outbound

This paper cites Differential Privacy-enabled Federated Learning for Sensitive Health Data.

Upcycling Noise for Federated Unlearning Differential Privacy-enabled Federated Learning for Sensitive Health Data

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.931901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85164e09-6b28-4671-a8e4-ff9d7e466023 · outbound

This paper cites Federated learning and differential privacy for medical image analysis,.

Upcycling Noise for Federated Unlearning Federated learning and differential privacy for medical image analysis,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.938090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f48fa5aa-fd62-4e14-9d92-55083489fd4c · outbound

This paper cites Federated quantum machine learning with differential privacy,.

Upcycling Noise for Federated Unlearning Federated quantum machine learning with differential privacy,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.358872Z

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 a43665e0-671b-4676-aefd-c8a395605d3c · outbound

This paper cites Concentrated differential privacy: Simplifications, extensions, and lower bounds,.

Upcycling Noise for Federated Unlearning Concentrated differential privacy: Simplifications, extensions, and lower bounds,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.948687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa24e83c-be71-4c55-bfcf-1308f569e88d · outbound

This paper cites Independent component analysis in the presence of gaussian noise by maximizing joint likelihood,.

Upcycling Noise for Federated Unlearning Independent component analysis in the presence of gaussian noise by maximizing joint likelihood,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.329158Z

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 b3811597-10da-4455-b1dc-dac656480cf2 · outbound

This paper cites The value of collaboration in convex machine learning with differential privacy,.

Upcycling Noise for Federated Unlearning The value of collaboration in convex machine learning with differential privacy,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.311718Z

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 f5865211-c00e-417f-98ca-5850ab0360a4 · outbound

This paper cites Strategic Data Revocation in Federated Unlearning.

Upcycling Noise for Federated Unlearning Strategic Data Revocation in Federated Unlearning

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-11T20:44:15.073931Z

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 e9147450-f388-4844-99c7-313845833777 · outbound

This paper cites Membership inference attacks against machine learning models,.

Upcycling Noise for Federated Unlearning Membership inference attacks against machine learning models,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.968942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49426451-eb98-45bc-90c0-8b35f08c6742 · outbound

This paper cites Becker and R.

Upcycling Noise for Federated Unlearning Becker and R

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.974435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5473b50d-e603-4ca9-8827-f35b8f6c5cd6 · outbound

This paper cites Acquire valued shoppers challenge,.

Upcycling Noise for Federated Unlearning Acquire valued shoppers challenge,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:44:15.275404Z

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 26ee0f61-0583-4211-b85c-1f4c0cb2d3bc · outbound

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

Upcycling Noise for Federated Unlearning Gradient-based learning applied to document recognition,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.985434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ffee009-8733-4d2b-83db-49c5ea9411ce · outbound

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

Upcycling Noise for Federated Unlearning Learning multiple layers of features from tiny images,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T20:44:14.990803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.