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Paper Citation Record · LEDGER

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data

As of 22 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2506.16723.

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

pith.paper-citation-record.v1
2506.16723 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:25:31.525148Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

38 of 38 outbound references displayed

  • verified exact1
  • verified fuzzy18
  • unresolved19
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b248152b-d200-435c-ac48-249e3a555aaa · outbound

This paper cites Ai-aided geometric design of anti-infection catheters,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Ai-aided geometric design of anti-infection catheters,

Reference 1

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation c16c951b-3fa3-4fdf-b965-0b74d5399a2f · outbound

This paper cites The value of standards for health datasets in artificial intelligence- based applications,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data The value of standards for health datasets in artificial intelligence- based applications,

Reference 2

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Source-reported events for the cited work

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Observation dcd1fbfd-bc63-443b-a6df-7e4918867d48 · outbound

This paper cites Hipaa regulations: a new era of medical-record privacy?.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Hipaa regulations: a new era of medical-record privacy?

Reference 3

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T19:25:31.387887Z digest=sha256:63daab9984ba6232857856ebfcd838c9c191f9003319fe0220edea2159776fe3

Observation 767afa97-5a3c-470c-acfe-cf98073e4d4d · outbound

This paper cites General data protection regulation (gdpr),.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data General data protection regulation (gdpr),

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation b30ffd5c-806c-4729-8840-1fe0c454f5a5 · outbound

This paper cites Split learning on segmented healthcare data,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Split learning on segmented healthcare data,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation e4b0e65c-53cf-46cd-b1f2-65daaec76416 · outbound

This paper cites Advances and open problems in federated learning,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Advances and open problems in federated learning,

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e83a57f3-52bb-4fae-9d28-e6f6193c4297 · outbound

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

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Communication-efficient learning of deep networks from decentralized data,

Reference 7

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source=pdf_text observed=2026-08-15T19:25:31.405788Z digest=sha256:f1e69ed5518b2faf7651efb1c6ba461277ec2332ee61441c8208e93eb601c5b1

Observation f8f354a8-aeeb-4c99-99bd-9222389c33a0 · outbound

This paper cites Distributed deep learning networks among institutions for medical imaging,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Distributed deep learning networks among institutions for medical imaging,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 3c4124fa-7d20-4a62-86f3-59528c3d25a8 · outbound

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

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Federated learning on non-iid data: A survey,

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:25:31.413790Z digest=sha256:00be6eb163c65d73f0ed3f134130f7f2a7b7f67b5824e631488ff81ff524f988

Observation a992a388-3eb7-40bc-aeec-b1033261cdb4 · outbound

This paper cites Split learning for health: Distributed deep learning without sharing raw patient data.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Split learning for health: Distributed deep learning without sharing raw patient data

Reference 10

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Unavailable: canonical work link unavailable.

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Observation 44b30889-7149-48ba-bfbf-d986406ff92d · outbound

This paper cites Rethinking architecture design for tackling data heterogeneity in federated learning,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Rethinking architecture design for tackling data heterogeneity in federated learning,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a854048e-e2cc-4f3f-9ac0-5af1a39b217f · outbound

This paper cites Federated learning technology in serial topology for iot networks,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Federated learning technology in serial topology for iot networks,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T19:25:31.426078Z digest=sha256:89b659c4206b67a74bf8ea5ba4f966a40bc2be056ab6ff76134185e227ecafdc

Observation f3228438-933c-4ece-a1e1-63742965e727 · outbound

This paper cites {PrivateFL}: Accurate, differentially private federated learning via personalized data transfor- mation,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data {PrivateFL}: Accurate, differentially private federated learning via personalized data transfor- mation,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T19:25:31.430009Z digest=sha256:e265fe1d5ab2f9047ab69d40d45e3d7b72990bf9ddfe07dc7653479a9ae5cc29

Observation 2c6b1063-ae2d-425d-9912-fc69ff2782fc · outbound

This paper cites Split Ways: Privacy-Preserving Training of Encrypted Data Using Split Learning.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Split Ways: Privacy-Preserving Training of Encrypted Data Using Split Learning

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T19:25:31.433876Z digest=sha256:58cc24d9c069fa967773a184a10f40378339ba6914bdaa5b02ee78465888bb4c

Observation 9b4bb0ea-9313-4720-89dd-9ccd1ebf05c5 · outbound

This paper cites A principled approach to data valuation for federated learning,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data A principled approach to data valuation for federated learning,

Reference 15

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source=pdf_text observed=2026-08-15T19:25:31.437909Z digest=sha256:e395f3b74d1f62c1b9d5fc0797dc98fcc341f93654b68a3be7d072970a18a0e1

Observation c01d7443-8c4a-47ce-84a4-531eab3883e0 · outbound

This paper cites Shapleyfl: Robust federated learning based on shapley value,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Shapleyfl: Robust federated learning based on shapley value,

Reference 16

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source=pdf_text observed=2026-08-15T19:25:31.441654Z digest=sha256:09b01bac658d00b9428e03f53e31912cae93941366434eba28978472671e7e9a

Observation 1678346a-fd8f-41a4-ba40-568824828e89 · outbound

This paper cites Federated optimization in heterogeneous networks,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Federated optimization in heterogeneous networks,

Reference 17

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source=pdf_text observed=2026-08-15T19:25:31.445191Z digest=sha256:81873599b939298ce92203471df981e1e56ee00a74dac914316f437628e8f23d

Observation 26c40594-a4b1-4092-a4f1-e894f2c879a9 · outbound

This paper cites Scaffold: Stochastic controlled averaging for federated learn- ing,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Scaffold: Stochastic controlled averaging for federated learn- ing,

Reference 18

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Observation 94490352-8b2f-4708-85db-2dd611fd94fd · outbound

This paper cites Feddisco: Fed- erated learning with discrepancy-aware collaboration,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Feddisco: Fed- erated learning with discrepancy-aware collaboration,

Reference 19

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Observation 8924e7aa-a802-45b7-9a7d-fc1bb4fd8af1 · outbound

This paper cites Fedlabx: a practical and privacy-preserving framework for federated learning,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Fedlabx: a practical and privacy-preserving framework for federated learning,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 7e0f0450-c08f-4ca7-887d-8979ca22b456 · outbound

This paper cites Tackling the objective inconsistency problem in heterogeneous federated optimiza- tion,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Tackling the objective inconsistency problem in heterogeneous federated optimiza- tion,

Reference 21

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Unavailable: canonical work link unavailable.

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Observation e0c85b20-f257-4531-bff7-f022c6262c57 · outbound

This paper cites Multi- institutional deep learning modeling without sharing patient data: A feasibility study on brain tumor segmentation,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Multi- institutional deep learning modeling without sharing patient data: A feasibility study on brain tumor segmentation,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation e729fa91-238c-4805-a02d-70fb7e866e58 · outbound

This paper cites Distributed learning of deep neural network over multiple agents,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Distributed learning of deep neural network over multiple agents,

Reference 23

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Unavailable: canonical work link unavailable.

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Observation 2707e5c0-12d1-4f29-a307-43e27aa97243 · outbound

This paper cites Decentralized federated learning: A survey and perspective,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Decentralized federated learning: A survey and perspective,

Reference 24

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Unavailable: canonical work link unavailable.

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Observation 5d91def4-3ea9-475c-8671-5761e259c4eb · outbound

This paper cites Peer-to-peer federated continual learning for naturalistic driving action recognition,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Peer-to-peer federated continual learning for naturalistic driving action recognition,

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 0498736c-c7f9-4482-abf4-d2474b6dfb15 · outbound

This paper cites Splitfed: When federated learning meets split learning,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Splitfed: When federated learning meets split learning,

Reference 26

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raw_fallback, observed 2026-08-15T19:25:31.830510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 951ab322-97ad-4411-bafc-d988676da05f · outbound

This paper cites Deep leakage from gradients,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Deep leakage from gradients,

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4bb4f2a7-ca8c-4648-9393-cde565d1f76e · outbound

This paper cites Unleashing the tiger: Inference attacks on split learning,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Unleashing the tiger: Inference attacks on split learning,

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8ac14cd9-faf7-41f6-a488-a4f0abf5cd34 · outbound

This paper cites Split without a leak: Reduc- ing privacy leakage in split learning,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Split without a leak: Reduc- ing privacy leakage in split learning,

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-15T19:25:31.801193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 78240d08-0f79-48d8-915f-9a2225127caf · outbound

This paper cites Improving prediction of blood cancer using leukemia microarray gene data and chi2 features with weighted convo- lutional neural network,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Improving prediction of blood cancer using leukemia microarray gene data and chi2 features with weighted convo- lutional neural network,

Reference 30

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raw_fallback, observed 2026-08-15T19:25:31.788277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 1cad3d56-0a3f-4e2f-9a19-4516790c6e16 · outbound

This paper cites Bioinformatics analysis of potential core genes for glioblastoma,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Bioinformatics analysis of potential core genes for glioblastoma,

Reference 31

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raw_fallback, observed 2026-08-15T19:25:31.775693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation e72a342a-ac1e-46c1-b587-77de534feb43 · outbound

This paper cites Cumida: An extensively curated microarray database for benchmarking and testing of machine learning approaches in cancer research,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Cumida: An extensively curated microarray database for benchmarking and testing of machine learning approaches in cancer research,

Reference 32

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Unavailable: canonical work link unavailable.

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Observation c849ce30-768e-4b93-9425-0e507f2a1572 · outbound

This paper cites A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns,

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation b9d99f3c-3301-42f8-b352-3ae5f2b13bcb · outbound

This paper cites The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a882442a-324b-49de-8529-fca13ec65d4f · outbound

This paper cites Deep residual learning for image recognition,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Deep residual learning for image recognition,

Reference 35

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unresolved
no resolver link, observed 2026-08-15T19:25:31.513431Z

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Observation c6b1cf5c-a715-48b6-b0a8-639cf414a147 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Adam: A Method for Stochastic Optimization

Reference 36

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unresolved
no resolver link, observed 2026-08-15T19:25:31.517345Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T19:25:31.517345Z digest=sha256:c07f878ecaf5e0cacb130a2e1dbe8b195feff6312eeec2e4ddf471a82fc7e311

Observation 5a2a0f5e-68cf-4762-9c29-008573b2aea4 · outbound

This paper cites Model-contrastive federated learning,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Model-contrastive federated learning,

Reference 37

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unresolved
no resolver link, observed 2026-08-15T19:25:31.521425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:25:31.521425Z digest=sha256:563a7775724cb3f665c03caafe92bce3189aaeda0c725109da6e7dedfa7b0e0d

Observation e421c280-4592-4174-98d7-5a51477a7039 · outbound

This paper cites Face recognition using pca and svm,.

TriCon-SF: A Triple-Shuffle and Contribution-Aware Serial Federated Learning Framework for Heterogeneous Healthcare Data Face recognition using pca and svm,

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-15T19:25:31.725503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T19:25:31.525148Z digest=sha256:2cda61f73160cece4ad61c06bde11aeb11e3ee9bf5d4c71eacfcd39668091dc0

Pith citing papers

No inbound Pith citation observations are available.