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Paper Citation Record · LEDGER

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

As of 8 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 2026-08-07T06:34:17.273281+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
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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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.119915Z digest=sha256:0756f61f7a7c020cee76bf60fb9a3f2b83c441cb3b69923ef96d0f35a268f586

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.125381Z digest=sha256:1dcdaa6b32e29df0dc22eac2cc9c656a91035186029b3a0a80b3053ab04839e3

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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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.131158Z digest=sha256:a2b6e94b758ad4b0f7f4177cfed7eddebf1706f178b9d8d683de72aa5a7b05de

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=sha256:7b2c644d4c1d61181907575a1c0f1d78037f964be69bbb9efe482b22bb2a4069

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=sha256:90b4e5a381f675cc52b316df930786d7cd91ca5f4847a55228ff63d7fbb5c5e8

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 2026-08-07T06:34:17.273281+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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no resolver link, observed 2026-08-06T22:59:37.152306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.152306Z digest=sha256:081c6deb5a693e78e86696098f4f075fe70c650cf4e0cf78a9315a12a60b158d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.157451Z digest=sha256:1cf502117b977a21ba5de855004e50c585b06ce5c1648a3f6face7fe690a3d83

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.162021Z digest=sha256:610beaf70bc98bbe7b5a88d5b63782cc6624b2217737f4697c3e6d30391f2314

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

Resolution
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.166871Z digest=sha256:537e78d530f516ac19059f615872bc831dddc65bbf514aa068e45289e4d4644a

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

Resolution
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.171589Z digest=sha256:cb3331d6421409d9b2efa5d7812a23784b2fb992757b3fdefe5305d7cbcbaa83

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.176207Z digest=sha256:8f3eb8ce5e894747630793f948721aa96c847da9d8c1bfdbe636d4928f11e7be

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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no resolver link, observed 2026-08-06T22:59:37.181966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:37.181966Z digest=sha256:48cc8bb8d4dbe37cd96d75fcdbf4cc8bf25926f7da043dfcc4803b91ee6dce9d

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 2026-08-07T06:34:17.273281+00:00.

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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 2026-08-07T06:34:17.273281+00:00.

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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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.196244Z digest=sha256:fb7bfe7bfe6f49e41356f1a033e96012ab9cf382722dc622d106dcc27802f14d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.201003Z digest=sha256:eb67bbe389d56300961d5f5b9bf4eea07576f396d56f594cb1a8591a8d1aaa33

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.205436Z digest=sha256:d39bc7e592851b74c86d4daf72c0f6e205a646f13887f8185fa45d28e5d8388f

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

Resolution
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=sha256:76d3b21450fa227964e83d1e02dc98fb87d85e4e01153c7f7f8e8b21d1b872fa

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.214452Z digest=sha256:a9f2385198d12adbca40a405a55d5739cf63dd147be75af1f1b647d1a881f454

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=sha256:5a105a4cc7db99cfa49b5f9c1df86fbe5411a2c76fa4077ef56b9c7d0f8333f5

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.225143Z digest=sha256:dc079bb90c7ae3cf4242ab43484a6ad60300deaaac30a44e5ff496fcc1b03759

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.229882Z digest=sha256:e99fb6e97313ed6f7c35d04869ca16ca79c496a5f796da8331f09729ac562534

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.235183Z digest=sha256:07bd34266e5c35b46caac20355e896835aed62f27eb61987a267962e0c15fcd7

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.240456Z digest=sha256:4849cb2effde1418fd26d2c300525bcdb585c2cf23d32e18875d15044f7c2f01

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.245851Z digest=sha256:8ace160ec9281d8c0ff2e9bd02c59f07f816496fba72e91048fdf03412c39e28

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.250780Z digest=sha256:65e164568706ee5238fbf9d0856372da574d8b52997c773143d235abb568fa2e

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.255957Z digest=sha256:9203e1689ae0a90a80a2afd194cbf3aeb3eeae152a92fc096c1821d7d12416f3

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.260421Z digest=sha256:ddf6ab7b49a59630df22805cffda75c919a3d17f94c5425712937b3137f65b41

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.265256Z digest=sha256:26852de2bbdbb8f358ab8f2abdbd1b99b12da1d4cb24f3c8793c99f980efd3eb

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.270408Z digest=sha256:009e15382ef5424db22c1d2a0b53963f7ffc91a9fc76dd11f4ad31a102d770ea

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.274930Z digest=sha256:f6f2ff1f8c5d521755b5aeba59c9a2164012cc8c68007defe2ad9d5d7c21a099

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.279699Z digest=sha256:d6755ae20ea4b256440ef4605d7afec51ab386e50ba721777a39c9c2530c7933

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.284091Z digest=sha256:7b6126701646c19e1b18b93de4fb789c51bbe94ea38cf50bf71ce653b0c4188d

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:dbc92d2fd936e8b5ffacadc05451b6e056726fcf72da2176fb13b0deb347d2b8

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:cbc937e9583316fe209c7cf6dfbb9f6dbe49a1c5f46e0ea30b3e76dde95b2e0b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.299158Z digest=sha256:a726310621978c972ea0c9e56152d2d4664e8d0bb4efedba79d6098a0fedd5c2

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.303533Z digest=sha256:339fee8217f22de946635257382b30a88883b5ae0ba475549cecf11d41af3f85

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.308064Z digest=sha256:38309abb393afdf3f782303f8baf977df654b9801260c609f87c2f2d4d5a20c6

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.312777Z digest=sha256:6a9a566c4485a493a964adb32144ff508cd30ef3fb3a4aea0b70faef3014cdcb

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=sha256:69547fabd7df9e4ba777dda899b90af9770c7c6576ca55ad48ec8dfddd0603ef

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=sha256:7064ba8ef84567eb331b245a142b9c9e7047d1e1a208066be6998ccea3804222

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.328435Z digest=sha256:dbe6df3ca26e306c770584947d2912929f70cd2278e56b9838bc24f0b7ed7a96

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:59:37.333519Z digest=sha256:88173b0be27094db690fd7b620dadfaee4cf91b9df47e6b24beb2ba18d329c9a

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T16:32:04.350053Z digest=sha256:690ac542eb8f4d4eab9090952c55c57671414e7eb8dea5195cd129792e059a07