Paper Citation Record · LEDGER

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning?

As of 22 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 2 inbound Pith citation observations for arXiv:2412.07813.

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

pith.paper-citation-record.v1
2412.07813 v3

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:02:47.085094Z

measured 33 of 33 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:19:14.788824Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T07:47:10.405071Z

Reference resolution

31 of 31 outbound references displayed

verified exact0
verified fuzzy27
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3ecc9794-f621-4921-aa2f-d70929bd8169 · outbound

This paper cites Federated Learning- Empowered Mobile Network Management for 5G and Beyond Net- works: From Access to Core,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Federated Learning- Empowered Mobile Network Management for 5G and Beyond Net- works: From Access to Core,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.380427Z

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.

Observation a6342ee9-21c6-48c7-9f4c-3c9e6a7134d2 · outbound

This paper cites SplitFed: When Federated Learning Meets Split Learning,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? SplitFed: When Federated Learning Meets Split Learning,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.371257Z

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.

Observation 5a8d565b-b916-4017-b422-069ee73fed84 · outbound

This paper cites Detailed comparison of communication efficiency of split learning and federated learning.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Detailed comparison of communication efficiency of split learning and federated learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T19:02:47.005263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 773daf30-d5ab-40f3-ad64-19ff3fbcc7e9 · outbound

This paper cites Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges and Future Directions,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges and Future Directions,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.362295Z

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.

Observation 703e169c-8da0-4d3f-8559-858911ff6c45 · outbound

This paper cites Accelerating Federated Learning with Split Learning on Locally Generated Losses,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Accelerating Federated Learning with Split Learning on Locally Generated Losses,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.353536Z

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.

Observation fc685ec2-6f64-4868-9d03-31ef12503d20 · outbound

This paper cites Split Learning Over Wireless Networks: Parallel Design and Resource Management,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Split Learning Over Wireless Networks: Parallel Design and Resource Management,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.345330Z

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.

Observation 99dac147-618d-48a5-b9fb-54e98537f433 · outbound

This paper cites Communication and Storage Efficient Federated Split Learning.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Communication and Storage Efficient Federated Split Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T19:02:47.018984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85427cda-c4a7-4413-8dc3-d1447c0ca966 · outbound

This paper cites Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networks,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.336861Z

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.

Observation 85502f3d-a46b-4456-a0b2-d326a80499a6 · outbound

This paper cites A Survey of In- centive Mechanism Design for Federated Learning,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? A Survey of In- centive Mechanism Design for Federated Learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.328757Z

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.

Observation 0d37969c-349a-41a8-bace-06968f8397d6 · outbound

This paper cites ESFL: Efficient Split Federated Learning over Resource-Constrained Heterogeneous Wireless Devices,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? ESFL: Efficient Split Federated Learning over Resource-Constrained Heterogeneous Wireless Devices,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.320826Z

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.

Observation 65c72b4b-0525-4f59-9f06-54fffd36c4ef · outbound

This paper cites Split Federated Learning-Empowered Energy-Efficient Mobile Traffic Prediction Over UA Vs,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Split Federated Learning-Empowered Energy-Efficient Mobile Traffic Prediction Over UA Vs,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.312808Z

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.

Observation 220d1232-1b5e-4db5-9b96-babb3cf076cf · outbound

This paper cites Multiple Classification with Split Learning,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Multiple Classification with Split Learning,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.305171Z

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.

Observation 8c96f3be-04b6-4585-9b31-916c21fa9444 · outbound

This paper cites Reducing Leakage in Distributed Deep Learning for Sensitive Health Data,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Reducing Leakage in Distributed Deep Learning for Sensitive Health Data,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.296792Z

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.

Observation ea9b10b9-e786-4eb6-b612-c07b7aa056e3 · outbound

This paper cites Exploring the Privacy-Energy Consumption Tradeoff for Split Federated Learning,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Exploring the Privacy-Energy Consumption Tradeoff for Split Federated Learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.288036Z

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.

Observation 2ba1649c-4761-430c-837a-5d18519f9539 · outbound

This paper cites Optimizing Privacy and Latency Tradeoffs in Split Federated Learning over Wireless Networks,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Optimizing Privacy and Latency Tradeoffs in Split Federated Learning over Wireless Networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.279103Z

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.

Observation a2403aeb-246a-4738-aa2e-eb19d915a97b · outbound

This paper cites When MiniBatch SGD Meets SplitFed Learning:Convergence Analysis and Performance Evaluation.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? When MiniBatch SGD Meets SplitFed Learning:Convergence Analysis and Performance Evaluation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T19:02:47.044732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cc0a6ba-51dd-4226-a719-902de51c0a5f · outbound

This paper cites User Preference Based Energy-Aware Mobile AR System with Edge Computing,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? User Preference Based Energy-Aware Mobile AR System with Edge Computing,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.270036Z

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.

Observation 0d7820e3-ee1a-494c-af3e-309b11bc37dd · outbound

This paper cites An Edge Network Orches- trator for Mobile Augmented Reality,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? An Edge Network Orches- trator for Mobile Augmented Reality,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.261028Z

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.

Observation c9849a07-30d1-4b63-b0c5-7249d389e956 · outbound

This paper cites Market model and optimal pricing scheme of big data and Internet of Things,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Market model and optimal pricing scheme of big data and Internet of Things,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.252165Z

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.

Observation 2232848e-bd0c-4614-905d-0db0c58eceab · outbound

This paper cites HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.242605Z

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.

Observation 0ab17cd3-7d8b-401a-aab3-3e556ca8af74 · outbound

This paper cites A Novel Joint Dataset and Computation Management Scheme for Energy-Efficient Federated Learning in Mobile Edge Computing,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? A Novel Joint Dataset and Computation Management Scheme for Energy-Efficient Federated Learning in Mobile Edge Computing,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.234014Z

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.

Observation b403f051-a9ae-404f-9c18-49f306ffc37a · outbound

This paper cites Joint Edge Server Selection and Dataset Management for Federated Learning-Enabled Mobile Traffic Prediction,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Joint Edge Server Selection and Dataset Management for Federated Learning-Enabled Mobile Traffic Prediction,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.225297Z

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.

Observation 4012b4d8-0292-4de7-9b00-f13fb9f172df · outbound

This paper cites Federated Learning over Wireless Networks: Optimization Model De- sign and Analysis,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Federated Learning over Wireless Networks: Optimization Model De- sign and Analysis,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.216948Z

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.

Observation 6722f81a-2c32-495b-92ad-ddffa2c95234 · outbound

This paper cites Basar and G.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Basar and G

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.208296Z

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.

Observation 2f0f3ce5-9e2b-4740-b524-54e004bb3697 · outbound

This paper cites an unresolved cited work.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:02:47.199107Z

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.

Observation 490c24d7-5e01-4bee-80e8-e775b15b085a · outbound

This paper cites Resource Pricing Game in Geo-distributed Clouds,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Resource Pricing Game in Geo-distributed Clouds,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.189876Z

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.

Observation fff61995-58ca-4991-a3d2-1c489471b50b · outbound

This paper cites Distributed Energy Trading in Microgrids: A Game-Theoretic Model and Its Equilibrium Analysis,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Distributed Energy Trading in Microgrids: A Game-Theoretic Model and Its Equilibrium Analysis,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.180048Z

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.

Observation 5557b7bb-9007-4451-a155-ffa72bb3aa7f · outbound

This paper cites Learning Multiple Layers of Features from Tiny Images,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Learning Multiple Layers of Features from Tiny Images,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.170478Z

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.

Observation fc8e4d92-adf1-4949-9586-526ad642ed54 · outbound

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

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.160909Z

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.

Observation f1d8d024-edc8-43cb-8a43-e65c12f216ad · outbound

This paper cites Decentralized Federated Learning Through Proxy Model Sharing,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? Decentralized Federated Learning Through Proxy Model Sharing,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.150979Z

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.

Observation 18eb9b9c-c934-46ee-8e48-145ad2e37914 · outbound

This paper cites The Algorithmic Foundations of Differential Privacy,.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? The Algorithmic Foundations of Differential Privacy,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:02:47.141076Z

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.

Pith citing papers

Observation 6cfb14a5-0a39-4252-a417-8e2778c70153 · inbound

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems cites this paper.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning?

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T05:19:14.788824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c385211-4fe6-4027-b064-20b27cd8e2e2 · inbound

Fast AI Model Partition for Split Learning over Edge Networks cites this paper.

Fast AI Model Partition for Split Learning over Edge Networks How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning?

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-19T07:47:10.407301Z

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.