Paper Citation Record · LEDGER

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning

As of 21 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 1 inbound Pith citation observation for arXiv:2507.07130.

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

pith.paper-citation-record.v1
2507.07130 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:13:22.702695Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T02:46:34.459345Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T22:26:13.827521Z

Reference resolution

49 of 49 outbound references displayed

verified exact0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cc70f505-c66a-4b47-8e3e-0e4c3f1bc3c5 · outbound

This paper cites Communication-Efficient Learning of Deep Networks from Decentralized Data,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Communication-Efficient Learning of Deep Networks from Decentralized Data,

Reference 1

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Observation 48370a9f-1008-4339-8487-0f1b7e86b83e · outbound

This paper cites Federated Optimiza- tion: Distributed Optimization Beyond the Datacenter,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Federated Optimiza- tion: Distributed Optimization Beyond the Datacenter,

Reference 2

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Observation 42955b8f-bef0-4e42-ab0c-97f6f8fe03ae · outbound

This paper cites Federated Optimization: Distributed Machine Learning for On-Device Intelligence.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Federated Optimization: Distributed Machine Learning for On-Device Intelligence

Reference 3

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Observation 461dd6a4-e42a-4e34-950c-40fd82831713 · outbound

This paper cites Federated Learning: Strategies for Improving Communication Efficiency.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Federated Learning: Strategies for Improving Communication Efficiency

Reference 4

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Observation 1e67f638-5d90-40e9-beb0-141ae5db9aba · outbound

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

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning SplitFed: When Federated Learning Meets Split Learning,

Reference 5

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Observation 8e6b2c1a-c577-41d4-88ff-ea4f105d7f01 · outbound

This paper cites BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systems,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systems,

Reference 6

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Observation ea06af95-15b3-42dd-82fd-727de8c020c3 · outbound

This paper cites C3-SL: Circular Convolution-Based Batch-Wise Compression for Communication- Efficient Split Learning,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning C3-SL: Circular Convolution-Based Batch-Wise Compression for Communication- Efficient Split Learning,

Reference 7

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Observation e204a302-1c95-42ff-80eb-0790d49f6980 · outbound

This paper cites Back-And-Forth Prediction for Deep Tensor Compression,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Back-And-Forth Prediction for Deep Tensor Compression,

Reference 8

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Observation a2cde4b6-e341-4e05-a8e7-9fa392a4ba7a · outbound

This paper cites Reducing Communication for Split Learning by Randomized Top-k Sparsification,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Reducing Communication for Split Learning by Randomized Top-k Sparsification,

Reference 9

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Observation 647224bd-c856-4986-aaf6-b5d4469ae0fa · outbound

This paper cites EcoFed: Efficient Communication for DNN Partitioning- Based Federated Learning ,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning EcoFed: Efficient Communication for DNN Partitioning- Based Federated Learning ,

Reference 10

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Observation 0b574e7c-0289-4300-b54f-f5c482cd07ce · outbound

This paper cites PiPar: Pipeline Parallelism for Collaborative Machine Learning,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning PiPar: Pipeline Parallelism for Collaborative Machine Learning,

Reference 11

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Observation efce2553-8b0a-4650-b7a5-5523067f9c14 · outbound

This paper cites SplitGP: Achieving Both Generalization and Personalization in Federated Learning,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning SplitGP: Achieving Both Generalization and Personalization in Federated Learning,

Reference 12

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Observation 96b63008-bb54-46c4-8155-bb67b4b456c0 · outbound

This paper cites Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge,

Reference 13

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Observation 09656b19-d1d8-4033-bec4-6b2f22a4df0b · outbound

This paper cites Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 14

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Observation 22758b9f-aa42-4e52-81c1-14b6fdc5ccc3 · outbound

This paper cites Federated Optimization in Heterogeneous Networks,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Federated Optimization in Heterogeneous Networks,

Reference 15

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Observation 8a6ab77c-f024-4984-b758-6a0507a23fe8 · outbound

This paper cites SCAFFOLD: Stochastic Controlled Averaging for Feder- ated Learning,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning SCAFFOLD: Stochastic Controlled Averaging for Feder- ated Learning,

Reference 16

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Observation 652208fb-2343-4418-8e98-3fbe5a69f403 · outbound

This paper cites Searching for MobileNetV3,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Searching for MobileNetV3,

Reference 17

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Observation 326e916f-2fde-4adb-a984-94ff45a81049 · outbound

This paper cites CIFAR-10 (Canadian Institute for Advanced Research),.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning CIFAR-10 (Canadian Institute for Advanced Research),

Reference 18

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Observation ea2d6c04-018a-4489-ac25-1b2ecfdc4f89 · outbound

This paper cites Learning Multiple Layers of Fea- tures from Tiny Images,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Learning Multiple Layers of Fea- tures from Tiny Images,

Reference 19

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Observation 4707c891-1cf8-42cb-af97-64f1428751be · outbound

This paper cites FedAdapt: Adaptive Offloading for IoT Devices in Federated Learning,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning FedAdapt: Adaptive Offloading for IoT Devices in Federated Learning,

Reference 20

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Observation 93ecfa01-e8be-4ebb-adff-c15922b02b01 · outbound

This paper cites Visualizing and Understanding Con- volutional Networks,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Visualizing and Understanding Con- volutional Networks,

Reference 21

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Observation ef816cdf-df51-4e4a-b644-87969848252e · outbound

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning How Transferable Are Features in Deep Neural Networks?

Reference 22

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Deep Learning,

Reference 23

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning On the Convergence of FedAvg on Non-IID Data,

Reference 24

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Observation aba6a8f7-c195-4942-a335-22e4755b5377 · outbound

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Decoupled Greedy Learning of CNNs,

Reference 25

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Optimization Methods for Large-Scale Machine Learning,

Reference 26

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Observation bdd629d8-530c-4ba8-9919-d2aa4e6fbac6 · outbound

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Training Neural Networks Using Features Replay,

Reference 27

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Observation b9bf4ee0-5859-4b40-b3ed-8c8ea9ada699 · outbound

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Communication- Efficient Algorithms for Statistical Optimization,

Reference 28

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Local SGD Converges Fast and Communicates Little,

Reference 29

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Sparsified SGD with memory,

Reference 30

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning,

Reference 31

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning A Stochastic Approximation Method,

Reference 32

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Scal- ability and Performance Evaluation of Edge Cloud Systems for Latency Constrained Applications,

Reference 33

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Very Deep Convolutional Net- works for Large-scale Image Recognition,

Reference 34

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Swin Transformer: Hierarchical Vision Transformer using Shifted Windows,

Reference 35

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning How to Train Your ViT? Data, Augmentation, and Regularization in Vision Transformers,

Reference 36

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale,

Reference 37

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning ImageNet Large Scale Visual Recognition Challenge,

Reference 38

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Federated Learning Based on Dynamic Regulariza- tion,

Reference 39

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Early Stopping—But When?

Reference 40

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Accelerating Federated Learning with Split Learning on Locally Generated Losses,

Reference 41

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning ParallelSFL: A Novel Split Federated Learning Framework Tackling Hetero- geneity Issues,

Reference 42

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This paper cites Hermes: An Ef- ficient Federated Learning Framework for Heterogeneous Mobile Clients,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Hermes: An Ef- ficient Federated Learning Framework for Heterogeneous Mobile Clients,

Reference 43

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This paper cites Billion-Scale Federated Learning on Mobile Clients: a Submodel Design with Tunable Privacy,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Billion-Scale Federated Learning on Mobile Clients: a Submodel Design with Tunable Privacy,

Reference 44

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning FedHD: Federated Learning with Hyperdimensional Computing,

Reference 45

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Understanding Deep Image Representations by Inverting Them,

Reference 46

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Observation 74a25c40-a478-4a51-bdd2-ca50b112d9c7 · outbound

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Deep Learning with Differential Pri- vacy,

Reference 47

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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Homomorphic Encryption for Arithmetic of Approximate Numbers,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:13:23.060067Z

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Observation d85aa615-2243-4630-97a9-f551001e1891 · outbound

This paper cites Certified Robustness to Adversarial Examples with Differential Privacy,.

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning Certified Robustness to Adversarial Examples with Differential Privacy,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:13:22.872679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation ec375b67-75a7-4143-bb97-a1d73bb3f0f5 · inbound

A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations cites this paper.

A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations Ampere: Communication-Efficient and High-Accuracy Split Federated Learning

Reference 175

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:26:13.829650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.