Paper Citation Record · LEDGER

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices

As of 18 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2507.17228.

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

pith.paper-citation-record.v1
2507.17228 v2

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:58:29.856095Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

46 of 46 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bc766592-ee27-4f10-a1aa-0498a9adc303 · outbound

This paper cites P3sl: Personalized privacy-preserving split learning on heterogeneous edge devices,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices P3sl: Personalized privacy-preserving split learning on heterogeneous edge devices,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:35.993818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bdf53569-2621-43fd-9136-01703890d585 · outbound

This paper cites Asteroid: Resource- efficient hybrid pipeline parallelism for collaborative dnn training on heterogeneous edge devices,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Asteroid: Resource- efficient hybrid pipeline parallelism for collaborative dnn training on heterogeneous edge devices,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:35.789742Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d68bf119-6dd8-46ca-8c62-07d4d4fb7b87 · outbound

This paper cites Deepiot: Compressing deep neural network structures for sensing systems with a compressor-critic framework,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Deepiot: Compressing deep neural network structures for sensing systems with a compressor-critic framework,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:35.524470Z

Source-reported events for the cited work

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Observation 366fc478-9148-4d45-b032-2c91e2158b5f · outbound

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

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Splitfed: When federated learning meets split learn- ing,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:35.317082Z

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Observation 5e3c0ca3-81e0-4a69-bdac-d9e587f8c4f4 · outbound

This paper cites On-device Training: A First Overview on Existing Systems.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices On-device Training: A First Overview on Existing Systems

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:58:30.435927Z

Source-reported events for the cited work

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Observation 52684d5f-298d-43fe-9b40-4ba749dd270f · outbound

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

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Distributed learning of deep neural network over multiple agents,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:35.098039Z

Source-reported events for the cited work

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Observation fdf89bea-0da0-4add-93fe-4ffe5bf04fbd · outbound

This paper cites Data-free one-shot federated learning under very high statistical heterogeneity,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Data-free one-shot federated learning under very high statistical heterogeneity,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:34.898011Z

Source-reported events for the cited work

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Observation 193bef02-01ca-44ea-85fe-d9f6a4b890ab · outbound

This paper cites Thapa, M.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Thapa, M

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:34.782980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6b1eda8e-f5d4-41c7-980a-d229fa76e37f · outbound

This paper cites End-to-end evaluation of feder- ated learning and split learning for internet of things,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices End-to-end evaluation of feder- ated learning and split learning for internet of things,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:34.647614Z

Source-reported events for the cited work

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Observation a5753080-883d-4347-8c2b-caeec6711410 · outbound

This paper cites Split learning in 6g edge networks,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Split learning in 6g edge networks,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:34.495931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0cfd57ad-58c8-40b7-80f3-9e384ae63e6e · outbound

This paper cites Vepakomma and R.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Vepakomma and R

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:34.318639Z

Source-reported events for the cited work

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Observation 3253f67f-8a48-48cf-b965-084f22ffb15d · outbound

This paper cites Improving the commu- nication and computation efficiency of split learning for iot appli- cations,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Improving the commu- nication and computation efficiency of split learning for iot appli- cations,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:34.176267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bcade690-7549-44d2-9491-ed00928db9dc · outbound

This paper cites Privacy-sensitive parallel split learning,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Privacy-sensitive parallel split learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:34.033754Z

Source-reported events for the cited work

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Observation 87194a6e-404d-4d48-a5d3-ad3f6f35c240 · outbound

This paper cites Inside the AI care home: the smart tech making old people safer,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Inside the AI care home: the smart tech making old people safer,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:33.897294Z

Source-reported events for the cited work

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Observation d194326e-2e55-4d15-9ca6-39deeeb00c97 · outbound

This paper cites Ares: Adaptive resource- aware split learning for internet of things,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Ares: Adaptive resource- aware split learning for internet of things,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:33.772969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 56c51354-a45a-4653-990f-45cf82e77c0b · outbound

This paper cites Adaptive split learning over energy-constrained wireless edge networks,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Adaptive split learning over energy-constrained wireless edge networks,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:33.586462Z

Source-reported events for the cited work

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Observation db5b361e-aa49-4d6c-bbac-8b57c8345be6 · outbound

This paper cites Resource-efficient Parallel Split Learning in Heterogeneous Edge Computing.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Resource-efficient Parallel Split Learning in Heterogeneous Edge Computing

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:58:30.254660Z

Source-reported events for the cited work

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Observation b68a4f98-037d-4016-8992-c566698d41f0 · outbound

This paper cites Unsplit: Data-oblivious model inversion, model stealing, and label inference attacks against split learning,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Unsplit: Data-oblivious model inversion, model stealing, and label inference attacks against split learning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:33.440268Z

Source-reported events for the cited work

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Observation eb18733f-821b-46a9-95c0-2dde517490be · outbound

This paper cites A review on bilevel optimization: From classical to evolutionary approaches and applications,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices A review on bilevel optimization: From classical to evolutionary approaches and applications,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:33.297287Z

Source-reported events for the cited work

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Observation ee625632-a9d9-4047-a969-ed1295c1b04d · outbound

This paper cites Constrained Bi-Level Optimization: Proximal Lagrangian Value function Approach and Hessian-free Algorithm.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Constrained Bi-Level Optimization: Proximal Lagrangian Value function Approach and Hessian-free Algorithm

Reference 20

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Source-reported events for the cited work

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Observation 2a40fd70-5384-4f8c-9e78-c3ac3429f1aa · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T14:58:27.640378Z

Source-reported events for the cited work

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Observation 0cd50877-b319-4d3a-be67-9281370e2b07 · outbound

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

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Learning multiple layers of features from tiny images,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T14:58:27.811657Z

Source-reported events for the cited work

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Observation 61227525-5837-4136-a04d-5481161218ce · outbound

This paper cites Automated flower classifi- cation over a large number of classes,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Automated flower classifi- cation over a large number of classes,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:33.143605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e665bcc8-c951-40bf-a36e-b337e64e6d15 · outbound

This paper cites Fsim: A feature similarity index for image quality assessment,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Fsim: A feature similarity index for image quality assessment,

Reference 24

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Source-reported events for the cited work

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Observation 07b6b981-3d8f-4417-9fbe-7f6a5a6e6934 · outbound

This paper cites Membership inference attacks from first principles,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Membership inference attacks from first principles,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:33.018236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 47fd095f-d31b-41be-ad32-976c28bcb2b9 · outbound

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

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Split learning for health: Distributed deep learning without sharing raw patient data

Reference 26

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Observation cb37b700-7e46-4ce7-9177-5069f3bb0961 · outbound

This paper cites Server-Side Local Gradient Averaging and Learning Rate Acceleration for Scalable Split Learning.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Server-Side Local Gradient Averaging and Learning Rate Acceleration for Scalable Split Learning

Reference 27

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Observation 43cd6282-df1e-435c-9301-1234a3dfe6ef · outbound

This paper cites Split Federated Learning Over Heterogeneous Edge Devices: Algorithm and Optimization.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Split Federated Learning Over Heterogeneous Edge Devices: Algorithm and Optimization

Reference 28

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Observation d0b793db-1673-4588-b42b-0cbfb2e1757e · outbound

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

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Unleashing the tiger: Inference attacks on split learning,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:32.899267Z

Source-reported events for the cited work

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Observation ee59897c-15ec-4411-93ef-86eb8b593bdf · outbound

This paper cites Get your foes fooled: Proximal gradient split learning for defense against model inversion attacks on iomt data,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Get your foes fooled: Proximal gradient split learning for defense against model inversion attacks on iomt data,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:32.731452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7654f23e-a23d-4cb8-a393-f7ba32b4bfcb · outbound

This paper cites Label leakage and protection in two-party split learning,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Label leakage and protection in two-party split learning,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:32.609514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0aae97a6-1b38-4f8a-8016-a5560b20d8d7 · outbound

This paper cites Prac- tical defences against model inversion attacks for split neural net- works,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Prac- tical defences against model inversion attacks for split neural net- works,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:32.455687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 69fcd6dc-dba6-4fb9-924a-58b346c25907 · outbound

This paper cites Recon- structing training data from trained neural networks,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Recon- structing training data from trained neural networks,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:32.286253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3ddba253-db0b-4869-ba73-b775e24e0657 · outbound

This paper cites Deep leakage from gradients,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Deep leakage from gradients,

Reference 34

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Source-reported events for the cited work

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Observation f567e64a-9547-4ce5-bd24-c0fc3cb3f671 · outbound

This paper cites Ppsfl: Privacy-preserving split federated learning for heterogeneous data in edge-based internet of things,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Ppsfl: Privacy-preserving split federated learning for heterogeneous data in edge-based internet of things,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:32.104774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d32648ea-f3ce-47b3-be67-21b4e70d9fb3 · outbound

This paper cites CURE: Privacy-Preserving Split Learning Done Right.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices CURE: Privacy-Preserving Split Learning Done Right

Reference 36

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Observation 71fa9bac-26dd-4982-8426-4d458b35c9c1 · outbound

This paper cites Split learning without local weight sharing to enhance client-side data privacy,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Split learning without local weight sharing to enhance client-side data privacy,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:31.942718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 07c30f22-906e-4860-87fe-a95b38b89535 · outbound

This paper cites Very deep convolutional net- works for large-scale image recognition,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Very deep convolutional net- works for large-scale image recognition,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:31.782853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 16b47548-6215-451c-9456-cbbf9335e695 · outbound

This paper cites Jetson nano - power- ful ai at your edge.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Jetson nano - power- ful ai at your edge

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:31.621814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 28dd0912-b1e9-4261-967a-d2a6b7ff14f9 · outbound

This paper cites Talbi, A Taxonomy of Metaheuristics for Bi-level Optimization.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Talbi, A Taxonomy of Metaheuristics for Bi-level Optimization

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:31.475116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 131ca2be-5477-4519-ba8a-967e51aa262e · outbound

This paper cites python-kasa: Python api for tp-link smarthome products.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices python-kasa: Python api for tp-link smarthome products

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:31.325816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4684c9b6-aece-461d-a269-01efdca27a38 · outbound

This paper cites Vta- smac: Variable traffic-adaptive duty cycled sensor mac protocol to enhance overall qos of s-mac protocol,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Vta- smac: Variable traffic-adaptive duty cycled sensor mac protocol to enhance overall qos of s-mac protocol,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:31.142133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e2265f18-52f0-4251-8d7e-e34860a246fe · outbound

This paper cites Gradient leak- age attacks in federated learning: Research frontiers, taxonomy, and future directions,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Gradient leak- age attacks in federated learning: Research frontiers, taxonomy, and future directions,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:30.947925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7846283e-68d3-4f39-9b0c-6ea598038a0b · outbound

This paper cites Mjolnir: Breaking the Shield of Perturbation-Protected Gradients via Adaptive Diffusion.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Mjolnir: Breaking the Shield of Perturbation-Protected Gradients via Adaptive Diffusion

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:58:30.033908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9b7caef2-0f70-4c2c-a323-972295bcb0bc · outbound

This paper cites U-shaped split federated learning: An efficient cross-device learning frame- work with enhanced privacy-preserving,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices U-shaped split federated learning: An efficient cross-device learning frame- work with enhanced privacy-preserving,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:30.776384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d19d4a26-fd2f-4ebd-86a3-dbe6f4292a59 · outbound

This paper cites Active client selection for clustered federated learning,.

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices Active client selection for clustered federated learning,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:58:30.603388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.