Paper Citation Record · LEDGER

Federated Unlearning Model Recovery in Data with Skewed Label Distributions

As of 14 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2412.13466.

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

pith.paper-citation-record.v1
2412.13466 v2

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:11:06.158140Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

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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

42 of 42 outbound references displayed

verified exact2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation df342aaa-947a-4ff3-ade8-820f7105dc94 · outbound

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

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Communication- efficient learning of deep networks from decentralized data

Reference 1

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Observation 058b2a1b-1a5f-4795-85b5-35784fdeb8cf · outbound

This paper cites A survey on federated learning.Knowledge- Based Systems, 216:106775, 2021.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions A survey on federated learning.Knowledge- Based Systems, 216:106775, 2021

Reference 2

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Observation eaa2787d-d08b-4bfa-9e43-e7c484c2e635 · outbound

This paper cites A survey on federated unlearning: Challenges, methods, and future directions.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions A survey on federated unlearning: Challenges, methods, and future directions

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:11:07.404953Z

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Observation 7131dc2e-5829-43ed-af5f-97ac84ba574d · outbound

This paper cites Federated Unlearning: A Survey on Methods, Design Guidelines, and Evaluation Metrics.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Federated Unlearning: A Survey on Methods, Design Guidelines, and Evaluation Metrics

Reference 4

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Observation 882e7331-2901-4bdc-9029-18c91b6aa21d · outbound

This paper cites A Survey on Federated Unlearning: Challenges and Opportunities.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions A Survey on Federated Unlearning: Challenges and Opportunities

Reference 5

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Observation 97b00df8-53ed-4ad8-a8fa-7700568fd41f · outbound

This paper cites Federated unlearning and its privacy threats.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Federated unlearning and its privacy threats

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:11:07.379729Z

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Observation 00496eeb-bfd6-45ef-84fb-1e85916302af · outbound

This paper cites Modeling global distribution for federated learning with label distribution skew.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Modeling global distribution for federated learning with label distribution skew

Reference 7

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Observation 128163b1-c905-42a4-976c-ff3bde52a871 · outbound

This paper cites Federated learning with label distribution skew via logits calibration.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Federated learning with label distribution skew via logits calibration

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:11:07.317576Z

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Observation 4a3fe97f-71eb-4481-af92-f4ee5b936e0f · outbound

This paper cites Fedrs: Federated learning with restricted softmax for label distribution non-iid data.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Fedrs: Federated learning with restricted softmax for label distribution non-iid data

Reference 9

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Observation 191812c5-fa64-45c0-8a38-6c8cb27b9ec9 · outbound

This paper cites QuickDrop: Efficient Federated Unlearning by Integrated Dataset Distillation.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions QuickDrop: Efficient Federated Unlearning by Integrated Dataset Distillation

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-11T13:11:06.403723Z

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Observation 2331dda3-6168-48d8-acf8-bf9faac5de5d · outbound

This paper cites Deepsmote: Fusing deep learning and smote for imbalanced data.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Deepsmote: Fusing deep learning and smote for imbalanced data

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:11:07.253015Z

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Observation 63b1a850-7116-4fbb-b8aa-1fa091b27cd2 · outbound

This paper cites The eu general data protection regulation (gdpr).A Practical Guide, 1st Ed., Cham: Springer International Publishing, 10(3152676):10–5555, 2017.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions The eu general data protection regulation (gdpr).A Practical Guide, 1st Ed., Cham: Springer International Publishing, 10(3152676):10–5555, 2017

Reference 12

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Observation 7e44bfcc-6b5d-4ce9-9159-d8d7bb94714c · outbound

This paper cites The california consumer privacy act of 2018.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions The california consumer privacy act of 2018

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:11:07.187099Z

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Observation 254d52ec-59c7-4b23-a6bf-4744845e4c8f · outbound

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

Federated Unlearning Model Recovery in Data with Skewed Label Distributions The right to be forgotten in federated learning: An efficient realization with rapid retraining

Reference 14

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Observation 687a0534-cb2b-43b9-b208-38c14cc3de07 · outbound

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

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Federated Unlearning: How to Efficiently Erase a Client in FL?

Reference 15

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Observation 3b7bc3e2-8289-40a2-957e-1dafe4ecebcb · outbound

This paper cites Federated unlearning: Guarantee the right of clients to forget.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Federated unlearning: Guarantee the right of clients to forget

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:11:07.128060Z

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Observation 75d79f22-d787-4a6c-9fde-d78ece1f98d4 · outbound

This paper cites Learn to Forget: Machine Unlearning via Neuron Masking.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Learn to Forget: Machine Unlearning via Neuron Masking

Reference 17

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Observation 99243288-9ee9-4e1e-a261-c2b7bf0e07cd · outbound

This paper cites Exact-fun: An exact and efficient federated unlearning approach.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Exact-fun: An exact and efficient federated unlearning approach

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:11:07.094016Z

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Observation 42a17178-36ce-44c0-8805-540c8841f588 · outbound

This paper cites Forget-svgd: Particle-based bayesian federated unlearning.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Forget-svgd: Particle-based bayesian federated unlearning

Reference 19

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Observation a6989471-3d30-4b8c-9164-8beb4c6ed211 · outbound

This paper cites Fedrecovery: Differentially private machine unlearning for federated learning frameworks.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Fedrecovery: Differentially private machine unlearning for federated learning frameworks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:11:07.036749Z

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Observation 5b429a33-1758-45e7-8e2a-c2ced7e053e8 · outbound

This paper cites Verifi: Towards verifiable federated unlearning.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Verifi: Towards verifiable federated unlearning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:11:06.997197Z

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Observation 07bdb259-f218-48a5-9303-30397afefc0f · outbound

This paper cites Sifu: Sequential informed federated unlearning for efficient and provable client unlearning in federated optimization.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Sifu: Sequential informed federated unlearning for efficient and provable client unlearning in federated optimization

Reference 22

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This paper cites Federated unlearning via class-discriminative pruning.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Federated unlearning via class-discriminative pruning

Reference 23

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This paper cites A state-of-the-art survey on solving non-iid data in federated learning.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions A state-of-the-art survey on solving non-iid data in federated learning

Reference 24

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Observation 0c67964a-9659-40a4-bf82-3895f78fe4f7 · outbound

This paper cites Federated learning on non-iid data silos: An experimental study.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Federated learning on non-iid data silos: An experimental study

Reference 25

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This paper cites Federated learning with non-iid data: A survey.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Federated learning with non-iid data: A survey

Reference 26

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This paper cites Robust and communication- efficient federated learning from non-iid data.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Robust and communication- efficient federated learning from non-iid data

Reference 27

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Observation bd3c3e7f-c6c8-45e4-8e31-992e59da55e9 · outbound

This paper cites Scaffold: Stochastic controlled averaging for federated learning.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Scaffold: Stochastic controlled averaging for federated learning

Reference 28

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This paper cites Model-contrastive federated learning.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Model-contrastive federated learning

Reference 29

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Federated Unlearning Model Recovery in Data with Skewed Label Distributions Data distribution-aware online client selection algorithm for federated learning in heterogeneous networks

Reference 30

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Federated Unlearning Model Recovery in Data with Skewed Label Distributions Adaptive federated learning on non-iid data with resource constraint

Reference 31

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This paper cites Federated learning enabled hotel customer classification towards imbalanced data.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Federated learning enabled hotel customer classification towards imbalanced data

Reference 32

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Federated Unlearning Model Recovery in Data with Skewed Label Distributions Federated Learning with Non-IID Data

Reference 33

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Federated Unlearning Model Recovery in Data with Skewed Label Distributions Distillation-based semi-supervised federated learning for communication-efficient collaborative training with non-iid private data

Reference 34

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This paper cites Towards asynchronous federated learning based threat detection: A dc-adam approach.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Towards asynchronous federated learning based threat detection: A dc-adam approach

Reference 35

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This paper cites Dynamic margin for federated learning with imbalanced data.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Dynamic margin for federated learning with imbalanced data

Reference 36

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Observation b7c0d537-1cbf-422e-8ff0-69bd2d7a4171 · outbound

This paper cites Lof: identifying density-based local outliers.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Lof: identifying density-based local outliers

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:11:06.635878Z

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Observation 5d07d23f-93e8-4aad-a2d8-33adac93ae3f · outbound

This paper cites Anomaly detection: A survey.

Federated Unlearning Model Recovery in Data with Skewed Label Distributions Anomaly detection: A survey

Reference 38

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Federated Unlearning Model Recovery in Data with Skewed Label Distributions Loci: Fast outlier detection using the local correlation integral

Reference 39

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

Federated Unlearning Model Recovery in Data with Skewed Label Distributions The mnist database of handwritten digit images for machine learning research [best of the web]

Reference 40

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Federated Unlearning Model Recovery in Data with Skewed Label Distributions Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 41

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Federated Unlearning Model Recovery in Data with Skewed Label Distributions Unresolved cited work

Reference 42

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Pith citing papers

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