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Paper Citation Record · LEDGER

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data

As of 9 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2506.20245.

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

pith.paper-citation-record.v1
2506.20245 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:59:37.333519Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T16:32:04.350053Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T16:34:16.359345Z

Reference resolution

48 of 48 outbound references displayed

  • verified exact2
  • verified fuzzy33
  • unresolved13
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0e97ffa8-ae78-4406-bbf4-0d8618925f7a · outbound

This paper cites Federated Learning with Personalization Layers.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Federated Learning with Personalization Layers

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ede9ad31-663a-4f3a-8b17-a1e58ef59a62 · outbound

This paper cites Federated learning with personalization layers.arXiv: Learning, 2019.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Federated learning with personalization layers.arXiv: Learning, 2019

Reference 2

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d2b6ae74-59e5-48cf-b25a-7f8eca6c354a · outbound

This paper cites Algorithms for hyper-parameter optimization.Ad- vances in neural information processing systems, 24, 2011.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Algorithms for hyper-parameter optimization.Ad- vances in neural information processing systems, 24, 2011

Reference 3

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation f145c2ef-c8bb-4cd7-88c6-829406737663 · outbound

This paper cites Federated learning with hierarchical clustering of local updates to im- prove training on non-iid data.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Federated learning with hierarchical clustering of local updates to im- prove training on non-iid data

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-06T22:59:38.126157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.114316Z digest=sha256:50818f520eb9856fb802cc2d70c5172b967d8b38584799c55e211a5eeafd5ab9

Observation abb31d6d-edd0-487a-af44-dbb1119292db · outbound

This paper cites LEAF: A Benchmark for Federated Settings.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data LEAF: A Benchmark for Federated Settings

Reference 5

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no resolver link, observed 2026-08-06T22:59:37.119915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.119915Z digest=sha256:028bef5d7965983ff3b7617b6b932df2db4d6d622c5df665f6c5de6bb0bf6d0f

Observation 2f6c1659-f7fe-4cc2-9e75-54b5dd82daf8 · outbound

This paper cites Personalized Federated Learning With Graph.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Personalized Federated Learning With Graph

Reference 6

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no resolver link, observed 2026-08-06T22:59:37.125381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.125381Z digest=sha256:3a377b6264a34e24edcf4cbba3c6edb86b0e3e527808dda5c6bc3c618a34617b

Observation 1f1c93f9-f393-4c73-8385-66476aa3d3fa · outbound

This paper cites Data-free learning of student networks.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Data-free learning of student networks

Reference 7

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raw_fallback, observed 2026-08-06T22:59:38.108244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.131158Z digest=sha256:584def64d6e54c5ab0a67c84c002dc2767683a82d6b0d63d1eddb7727015be07

Observation 873ff42b-9e81-43be-ac05-65ba20166b58 · outbound

This paper cites FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

Reference 8

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no resolver link, observed 2026-08-06T22:59:37.136885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.136885Z digest=sha256:11b94fd64ac2fde278aedf03b162934e28733fe5fcc586a2165d2985a2f71441

Observation eb358611-8d65-4489-98fd-94e1c064a464 · outbound

This paper cites On Bridging Generic and Personalized Federated Learning for Image Classification.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data On Bridging Generic and Personalized Federated Learning for Image Classification

Reference 9

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unresolved
no resolver link, observed 2026-08-06T22:59:37.142062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.142062Z digest=sha256:470358888a252ec70adfc96f04025b1f90a0a670d8936abfb88bb8757fb9d82d

Observation 4d696138-26be-4e1b-986f-f416d9cd2584 · outbound

This paper cites Fedmatch: Federated learning over heteroge- neous question answering data.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Fedmatch: Federated learning over heteroge- neous question answering data

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-06T22:59:38.092164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 6b60cf13-31c1-4cf9-a9dc-b0ed1447841a · outbound

This paper cites Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.152306Z digest=sha256:560aa6037b4d71bb5944def77400ab53f8d20c716f7d9ccc150ad661b3f40240

Observation bf254fa2-e99f-4c3d-bd93-c5b192e58c8a · outbound

This paper cites Exploiting shared representations for personal- ized federated learning.arXiv: Learning, 2021.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Exploiting shared representations for personal- ized federated learning.arXiv: Learning, 2021

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.157451Z digest=sha256:3ffa4e58ba8a93df8a57e29cec7f1d292daa1b402ed4e3fc7fa9349d92b6536a

Observation b7f3747b-1485-4c7b-8493-9bc80edfa94c · outbound

This paper cites Exploiting shared representations for personal- ized federated learning.arXiv: Learning, 2021.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Exploiting shared representations for personal- ized federated learning.arXiv: Learning, 2021

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:38.060065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.162021Z digest=sha256:44e446211f5a3a0c9d8979ef9635420382db3ff68e5c00f6ce6da8b25d363efa

Observation bf461381-ba51-4795-a9ea-5b10bdf9a1aa · outbound

This paper cites Adaptive personalized federated learning.arXiv: Learning, 2021.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Adaptive personalized federated learning.arXiv: Learning, 2021

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-06T22:59:38.042419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.166871Z digest=sha256:e4e0eb26a528dde301396f54fb0a3269b69b4cd9fc04bc971a829389162881d4

Observation 169f746a-e152-4836-a7a5-4d59981bfabd · outbound

This paper cites Dinh, Tung Thanh Vu, Nguyen H.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Dinh, Tung Thanh Vu, Nguyen H

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-06T22:59:38.025260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.171589Z digest=sha256:24f73b69605dd65f1cadddf4fca260e4991ae81f2c9cc966fe503a4ad0b6398e

Observation a0322c86-9ac7-4b3e-b66e-190b50d5ec32 · outbound

This paper cites Private semi- supervised federated learning.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Private semi- supervised federated learning

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:38.005015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.176207Z digest=sha256:b84e43fa34051266c8a9253c7aa79ae655d809803c129eb538f70c5b2954c0f3

Observation a4dd50ec-64f9-441d-a3c0-7d3c99ccd3a4 · outbound

This paper cites One-Shot Federated Learning.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data One-Shot Federated Learning

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.181966Z digest=sha256:2b253cc797e892870ca6884636a2e01821fd9c87351b38f35b6a4304c6526b2d

Observation 5fa715eb-145c-482f-8481-7937054b8ee2 · outbound

This paper cites Federated learning of a mixture of global and local models.arXiv: Learning, 2021.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Federated learning of a mixture of global and local models.arXiv: Learning, 2021

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.186865Z digest=sha256:5458cde2c8d8deb45777292bd725a1f3a0cf961db1aa1b7afbe8f2771099b894

Observation b2356bf4-f975-4c0b-b35c-1677610e3a02 · outbound

This paper cites Towards fair federated learning with zero-shot data augmentation.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Towards fair federated learning with zero-shot data augmentation

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.191632Z digest=sha256:65cda161e2885f0aecd718eb2851b1a713ba30a150db57cb19da75d022cf9687

Observation e22a4544-af40-40ef-b9e4-b7de1ab62ef7 · outbound

This paper cites Group knowledge transfer: Federated learning of large cnns at the edge.Advances in Neural Information Processing Sys- tems, 33:14068–14080, 2020.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Group knowledge transfer: Federated learning of large cnns at the edge.Advances in Neural Information Processing Sys- tems, 33:14068–14080, 2020

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.952897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.196244Z digest=sha256:5b32819a06bb6265bc4e6608e33e19a02bb1c2e60d5c32f13ee3e1bdc361d8a5

Observation 5fd7444e-37b9-4cfb-99d9-2eb2ea1dd9ad · outbound

This paper cites Personalized cross-silo federated learning on non-iid data.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Personalized cross-silo federated learning on non-iid data

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.936247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.201003Z digest=sha256:2c580633f83b8348143e51e0df9921a743421feb7d72641129eefa4daae1c1b8

Observation bfd1e3b0-6fa4-4372-9771-96e36645334c · outbound

This paper cites Personalized cross-silo federated learning on non-iid data.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Personalized cross-silo federated learning on non-iid data

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.916651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.205436Z digest=sha256:523c1733a0d3f51f68000cb89a46ac3d94cd137d4352f679e271b69db395490f

Observation efa68fa6-85ff-4a1d-bb13-b51699e68e51 · outbound

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

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Learning multiple layers of features from tiny images

Reference 23

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unresolved
no resolver link, observed 2026-08-06T22:59:37.209959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.209959Z digest=sha256:99d8d9f9bb96f632d37c2d79217d914e29ed791ee782f78be2321704326dbed5

Observation 67153077-3e9d-45da-b3a2-4181049916bc · outbound

This paper cites Sur- vey of personalization techniques for federated learning.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Sur- vey of personalization techniques for federated learning

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.889983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.214452Z digest=sha256:dfb4f76267ef42202907a2b8dbb5a91b33ac0e74869dea0fdd837a1428320955

Observation 2e010ee3-a1d7-4bb3-b496-955547203c8e · outbound

This paper cites FedMD: Heterogenous Federated Learning via Model Distillation.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data FedMD: Heterogenous Federated Learning via Model Distillation

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T22:59:37.219227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.219227Z digest=sha256:47725f441245b0a47d68330a73efb1872792b68802d4981bd4e09f4a5cc9c546

Observation 5401e78c-0d45-4417-b7ac-93a70e492429 · outbound

This paper cites Ditto: Fair and robust federated learning through personalization.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Ditto: Fair and robust federated learning through personalization

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.873637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.225143Z digest=sha256:8f60e4af8782267f9b5d39d49f4d3b58a05b45f9f7980edc3ecba85238432a92

Observation cbf02ce9-2d13-4595-8b3e-bbb094800bf2 · outbound

This paper cites Federated optimiza- tion in heterogeneous networks.Proceedings of Machine learning and systems, 2:429–450, 2020.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Federated optimiza- tion in heterogeneous networks.Proceedings of Machine learning and systems, 2:429–450, 2020

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.858368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.229882Z digest=sha256:01902c7853745663ae3346955382764884849c1f3dd0cc147603ff786fcaf4f5

Observation a5b1aa5d-0226-4621-87b7-ba84b4d309b6 · outbound

This paper cites FedDKD: Federated Learning with Decentralized Knowledge Distillation.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data FedDKD: Federated Learning with Decentralized Knowledge Distillation

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:59:37.465015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.235183Z digest=sha256:fd16ae24c22b25305a4426440b7454f7c510a7b4c01f51aefaf3c7e2a7a5516b

Observation 67d8274d-b5f0-4fa1-845d-4d8dc0f7775c · outbound

This paper cites Think locally, act glob- ally: Federated learning with local and global representa- tions.arXiv: Learning, 2020.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Think locally, act glob- ally: Federated learning with local and global representa- tions.arXiv: Learning, 2020

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.841918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.240456Z digest=sha256:b72bd41ef14201ab56edd9e876eb0d55c125ffd07e68abdbf7424db1311db94f

Observation 61051661-9275-438b-9065-7e1e6b9a2c4d · outbound

This paper cites Think locally, act glob- ally: Federated learning with local and global representa- tions.arXiv: Learning, 2020.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Think locally, act glob- ally: Federated learning with local and global representa- tions.arXiv: Learning, 2020

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.826160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.245851Z digest=sha256:794509d43ec5cabbca490389f5a7079f00d9047be357c1f0497a4f85e0c4930c

Observation 3f5b1218-200c-46cc-8b0d-9751fac9ea25 · outbound

This paper cites Ensemble distillation for robust model fusion in fed- erated learning.Advances in Neural Information Processing Systems, 33:2351–2363, 2020.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Ensemble distillation for robust model fusion in fed- erated learning.Advances in Neural Information Processing Systems, 33:2351–2363, 2020

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.810641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.250780Z digest=sha256:820140849c56706318d9ba1a7a8a4b6c30a7b7af7412409b3ec1eb2701e4ade3

Observation 221d46de-650a-4adf-91b5-f5538f46510a · outbound

This paper cites Federated learning for privacy- preserving open innovation future on digital health.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Federated learning for privacy- preserving open innovation future on digital health

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.795581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.255957Z digest=sha256:4c40b2935f5e7ef52de679a861b5aedd031f59467c64f4e7cbc8310018b1365e

Observation e2426f18-8044-4e71-a9ba-0498340c5cda · outbound

This paper cites Federated learning for open banking.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Federated learning for open banking

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.779146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.260421Z digest=sha256:9b005094462684c057f355a032fef7917b986a863b65fce542199efce74b8189

Observation ee1118f7-84fb-48fe-808d-78c287aa350e · outbound

This paper cites Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learning.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learning

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:59:37.442092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.265256Z digest=sha256:f6f755d17987a4e82303a0981f3b269cc4a3c733cd85d4375a29f90da582c679

Observation 5e27d9a4-9f82-41d2-8507-4a77c65aa53b · outbound

This paper cites Mode seeking generative adversarial networks for diverse image synthesis.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Mode seeking generative adversarial networks for diverse image synthesis

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.762855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.270408Z digest=sha256:93d7e807a20e30850572c1793191e34f709c3dceef52fd6a88887622bc2978b3

Observation 14eee79d-e7c3-436f-86af-258f572d682f · outbound

This paper cites Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.746144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.274930Z digest=sha256:f0581d8fd46190705499ab11d91142f52a959ec096dbd524a570aa1923f83d0b

Observation 7f176e21-5575-4e74-b6f6-e7f71ff791dd · outbound

This paper cites Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.730548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.279699Z digest=sha256:a8412ae21aea4f33610254e02117782c99ee1ccddca35bbadf9d4859b027e765

Observation aad1d10b-ed7f-48f7-84fa-6f8c0d629be7 · outbound

This paper cites Personalized federated learning using hypernetworks.arXiv: Learning, 2021.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Personalized federated learning using hypernetworks.arXiv: Learning, 2021

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.713682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.284091Z digest=sha256:23076e5c4426712eaf3c45c744dbf9e7afa8ef2199f843fd62d4a3a04677b935

Observation 8a3b456f-ceb6-4f39-aa00-85d8714e8fb1 · outbound

This paper cites Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T22:59:37.289056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.289056Z digest=sha256:ef8f8447e558a19e962c5938a63e07e33687c20b172067b4fd92f3bbec8d6a36

Observation de1a9ec0-dca9-4b50-92bf-0e0d77b181f7 · outbound

This paper cites Fed-ensemble: Improving Generalization through Model Ensembling in Federated Learning.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Fed-ensemble: Improving Generalization through Model Ensembling in Federated Learning

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T22:59:37.294041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.294041Z digest=sha256:bb80f5fca27250231c9c1fea2c63e5d8fbcd0e8ca6439cd35d9dad79dce4cc23

Observation 271e4473-c7d7-432e-b7e2-50781f8ade00 · outbound

This paper cites Feded: Federated learning via ensemble distillation for medical relation extraction.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Feded: Federated learning via ensemble distillation for medical relation extraction

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.697087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.299158Z digest=sha256:cb6e1dcb645ca5f3f02973ae45859c6303f3ede5d17b103b32e6f6e89dbe4342

Observation 762f3543-02b0-4456-9878-8603bd51703b · outbound

This paper cites Personalized federated learning with moreau envelopes.Advances in Neu- ral Information Processing Systems, 33:21394–21405, 2020.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Personalized federated learning with moreau envelopes.Advances in Neu- ral Information Processing Systems, 33:21394–21405, 2020

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.679261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.303533Z digest=sha256:4d0571f212bdb0ea0a0dc7c4ba8a13b79b989e3c54094a0bbd5746c685874db5

Observation 6673f7c4-d105-4037-827b-5a6a1574dc9d · outbound

This paper cites Personalized federated learning with contextualized generalization.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Personalized federated learning with contextualized generalization

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.662335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.308064Z digest=sha256:5fbfc101f93e847dd01262e1e5b75fc3c7f704d45dd4542e6733395af4d26059

Observation 709eaca4-26cb-4201-9fa0-f41397b5cfc3 · outbound

This paper cites Personal- ized federated learning by structured and unstructured prun- ing under data heterogeneity.arXiv: Learning, 2021.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Personal- ized federated learning by structured and unstructured prun- ing under data heterogeneity.arXiv: Learning, 2021

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.639555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.312777Z digest=sha256:7afb7647fdb517c71759d8e76047677511e77c036a961e5fe75e320b248e69db

Observation 805a1bc6-baf4-4bfa-9e74-f77b67d57664 · outbound

This paper cites Federated Learning with Matched Averaging.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Federated Learning with Matched Averaging

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T22:59:37.317856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.317856Z digest=sha256:ae58dc71ff241382989b9f5b925cc13d5d3353d4b98f7b041b388ecee3f1da92

Observation 4d1c7e3f-cd8a-4d03-8c1c-b8271c224d29 · outbound

This paper cites FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T22:59:37.323613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.323613Z digest=sha256:905b846a57508ab7dc11c75daeb7c1d6cc06e5d3fea65cefedd136f23b80cae1

Observation e42c1840-f8b1-4d6e-883f-a51a28b0169e · outbound

This paper cites Bayesian nonparametric federated learning of neural networks.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Bayesian nonparametric federated learning of neural networks

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.621600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.328435Z digest=sha256:0ecf6a1b9a5917d7bb8cc320f9403c70f43d1ffe452a53554a9514364a660709

Observation 4be9ba62-850f-41b9-84ff-370b8f288128 · outbound

This paper cites Data-free knowledge distillation for heterogeneous federated learning.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data Data-free knowledge distillation for heterogeneous federated learning

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:59:37.605698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:59:37.333519Z digest=sha256:687289d78345491bccab93f73ab4a1c0e27672e7fafad58e656838f131946a95

Pith citing papers

Observation 00cedbbf-fe25-410d-b66f-9fceb69859cc · inbound

Secure, Verifiable, and Scalable Multi-Client Data Sharing via Consensus-Based Privacy-Preserving Data Distribution cites this paper.

Secure, Verifiable, and Scalable Multi-Client Data Sharing via Consensus-Based Privacy-Preserving Data Distribution FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-21T16:34:16.361918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-21T16:32:04.350053Z digest=sha256:5ff958deccaf68e0e4e5314bcd7b3a9e3fb6d7dbd673ad15926bf37008c53d7f