Paper Citation Record · LEDGER

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems

As of 7 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 4 inbound Pith citation observations for arXiv:2506.08426.

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

pith.paper-citation-record.v1
2506.08426 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:19:18.778384Z

measured 59 of 59 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:24:39.944675Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T15:26:33.742902Z

Reference resolution

55 of 55 outbound references displayed

verified exact0
verified fuzzy46
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d0a6cc47-6d9a-46b3-bc3b-a341dbe1ad00 · outbound

This paper cites Optimiz- ing Parameter Mixing Under Constrained Communications in Parallel Federated Learning,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Optimiz- ing Parameter Mixing Under Constrained Communications in Parallel Federated Learning,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:22.135651Z

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.

Observation 9ecd958f-a29d-44b3-9bea-b4ea6e5120c1 · outbound

This paper cites HSplitLoRA: A Heterogeneous Split Parameter-Efficient Fine-Tuning Framework for Large Language Models.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems HSplitLoRA: A Heterogeneous Split Parameter-Efficient Fine-Tuning Framework for Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T05:19:12.409278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec085dda-b68c-43c5-8e5e-87667b13b23b · outbound

This paper cites Actions at the Edge: Jointly Optimizing the Resources in Multi-access Edge Computing,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Actions at the Edge: Jointly Optimizing the Resources in Multi-access Edge Computing,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:22.124881Z

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.

Observation 612aa001-0812-4ccd-b81b-54ad68405feb · outbound

This paper cites Federated Learning over Multihop Wireless Networks with In-network Aggregation,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Federated Learning over Multihop Wireless Networks with In-network Aggregation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:22.112311Z

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.

Observation e7523429-d371-443e-8e1a-8b262e5b5729 · outbound

This paper cites Communication-efficient Learning of Deep Networks From Decentral- ized Data,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Communication-efficient Learning of Deep Networks From Decentral- ized Data,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:22.101220Z

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.

Observation ac121246-1312-45e5-94ca-5fc186f1be8e · outbound

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

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Federated Learning: Strategies for Improving Communication Efficiency

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T05:19:12.809295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 202eab37-91c3-4267-8a56-2e649c2fd544 · outbound

This paper cites FedSN: A Federated Learning Framework over Heterogeneous LEO Satellite Networks,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems FedSN: A Federated Learning Framework over Heterogeneous LEO Satellite Networks,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:22.089137Z

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.

Observation 812f4e70-0520-4b88-b767-435c1ad4fa05 · outbound

This paper cites Accelerating Federated Learning with Model Segmentation for Edge Networks,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Accelerating Federated Learning with Model Segmentation for Edge Networks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:22.036747Z

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.

Observation 006ef0b5-57c1-47a2-8eec-c8faca2d4ff2 · outbound

This paper cites Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T05:19:13.077585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fdb6c9f-5907-43a2-89ef-fa34983b424f · outbound

This paper cites LEO-Split: A Semi-Supervised Split Learning Framework over LEO Satellite Networks.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems LEO-Split: A Semi-Supervised Split Learning Framework over LEO Satellite Networks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T05:19:13.180455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 221d8130-e133-4b28-968d-00bb404505f7 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Gemini: A Family of Highly Capable Multimodal Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T05:19:13.277342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3a65ad8-b5de-4ace-a499-7afe87a63600 · outbound

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

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Split learning for health: Distributed deep learning without sharing raw patient data

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T05:19:13.380159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f3bcc76-e2f3-4143-818c-4973a835f7f2 · outbound

This paper cites Pipelining Split Learning in Multi-hop Edge Networks,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Pipelining Split Learning in Multi-hop Edge Networks,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T05:19:13.473112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1eb26c1-063a-414f-aefe-030de3327735 · outbound

This paper cites Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunities,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunities,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.972220Z

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.

Observation a29e315f-6891-4f63-a888-0d4c65a58bd4 · outbound

This paper cites Optimal Resource Allocation for U-Shaped Parallel Split Learning,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Optimal Resource Allocation for U-Shaped Parallel Split Learning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.918270Z

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.

Observation f2df321a-2ec8-42d8-804e-f26e632cf10b · outbound

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

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Splitfed: When Federated Learning Meets Split Learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.886040Z

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.

Observation a0c05dc7-87b5-4dcc-857f-5fba8090eafa · outbound

This paper cites Distributed Learning in Wireless Networks: Recent Progress and Future Challenges,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Distributed Learning in Wireless Networks: Recent Progress and Future Challenges,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.868254Z

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.

Observation eb1da1af-d456-4e92-965d-d89e4f48e6e0 · outbound

This paper cites Time-sensitive Learning For Heterogeneous Federated Edge Intelligence,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Time-sensitive Learning For Heterogeneous Federated Edge Intelligence,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.851460Z

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.

Observation aa7e9649-4fcf-4dae-87fa-1c33b6df4bdb · outbound

This paper cites Speeding Up Distributed Machine Learning Using Codes,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Speeding Up Distributed Machine Learning Using Codes,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.832698Z

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.

Observation 375ef21c-40f1-440b-adda-c535f143a961 · outbound

This paper cites Split learning over Wireless Networks: Parallel Design and Resource Management,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Split learning over Wireless Networks: Parallel Design and Resource Management,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.815858Z

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.

Observation 9b81a4f8-2a76-4ed7-bcf5-2bd23b75cd99 · outbound

This paper cites AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T05:19:14.275914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning?.

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 9f661f07-6153-4783-bb48-8acac9e49563 · outbound

This paper cites Hi- erarchical Split Federated Learning: Convergence Analysis and System Optimization,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Hi- erarchical Split Federated Learning: Convergence Analysis and System Optimization,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.796292Z

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.

Observation 841ce698-9d8a-41a4-b7ae-1a09adb073e2 · outbound

This paper cites Adaptive Federated Learning in Resource Constrained Edge Computing Systems,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Adaptive Federated Learning in Resource Constrained Edge Computing Systems,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.775844Z

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.

Observation 6c1e59c9-1d6a-4061-8f79-4ebabaf997f9 · outbound

This paper cites Adaptive Batchsize Selection and Gradient Compression For Wireless Federated Learning,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Adaptive Batchsize Selection and Gradient Compression For Wireless Federated Learning,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.756187Z

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.

Observation 57a52eb5-b881-4046-a929-803ac82b1b7a · outbound

This paper cites Adaptive Batch Size For Federated Learning in Resource-constrained Edge Computing,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Adaptive Batch Size For Federated Learning in Resource-constrained Edge Computing,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.739916Z

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.

Observation 567b8293-6966-4165-8337-0d52d5b420a2 · outbound

This paper cites DYNAMITE: Dynamic Interplay of Mini-batch Size and Aggregation Frequency For Federated Learning with Static and Streaming Datasets,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems DYNAMITE: Dynamic Interplay of Mini-batch Size and Aggregation Frequency For Federated Learning with Static and Streaming Datasets,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.722528Z

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.

Observation 8052b08b-734b-4bf5-93ef-672aa3135444 · outbound

This paper cites To Talk or to Work: Dynamic Batch Sizes Assisted Time Efficient Federated Learning over Future Mobile Edge Devices,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems To Talk or to Work: Dynamic Batch Sizes Assisted Time Efficient Federated Learning over Future Mobile Edge Devices,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.703567Z

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.

Observation 51335f1b-492a-47bd-9b0a-e71128982769 · outbound

This paper cites Don’t Decay the Learning Rate, Increase the Batch Size,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Don’t Decay the Learning Rate, Increase the Batch Size,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.684740Z

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.

Observation 1d418a7c-5544-4f92-9286-7a6d85f1a808 · outbound

This paper cites On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-convex Optimization,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-convex Optimization,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.666811Z

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.

Observation 34184eca-cee7-4423-8f46-25c5c03e8ea2 · outbound

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

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.646009Z

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.

Observation 0d72df72-4a0b-4172-9f6d-72816efaf638 · outbound

This paper cites Convergence Analysis of Split Federated Learning on Heterogeneous Data,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Convergence Analysis of Split Federated Learning on Heterogeneous Data,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.628519Z

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.

Observation 4ddc86ad-e470-4eef-a5be-e5cb639b9975 · outbound

This paper cites Unleashing the Tiger: Inference Attacks on Split Learning,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Unleashing the Tiger: Inference Attacks on Split Learning,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.611964Z

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.

Observation 4d42c08c-8352-45da-a822-ed5f86db6aa7 · outbound

This paper cites On the Convergence Properties of A K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems On the Convergence Properties of A K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.594511Z

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.

Observation 7165684b-e905-4b9f-9592-3adc5536555a · outbound

This paper cites On the Linear Speedup Analysis of Communication Efficient Momentum SGD For Distributed Non-convex Optimization,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems On the Linear Speedup Analysis of Communication Efficient Momentum SGD For Distributed Non-convex Optimization,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.515224Z

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.

Observation 5f587a60-b491-448a-a392-4c7aeac51582 · outbound

This paper cites Scaffold: Stochastic Controlled Averaging for Federated Learn- ing,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Scaffold: Stochastic Controlled Averaging for Federated Learn- ing,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.370751Z

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.

Observation a9d56ab0-6058-4419-b92f-66efc8d1e430 · outbound

This paper cites Communication-efficient Algorithms for Statistical Optimization,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Communication-efficient Algorithms for Statistical Optimization,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.239009Z

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.

Observation fa1e06c5-21ed-4054-a885-cae1b0b37e7f · outbound

This paper cites Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.171479Z

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.

Observation 5c411f21-03ff-4da5-94b1-0a752c657cb4 · outbound

This paper cites Perturbed Iterate Analysis for Asynchronous Stochastic Optimization,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Perturbed Iterate Analysis for Asynchronous Stochastic Optimization,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.148655Z

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.

Observation 588b5520-5bb0-4af6-a308-7c27ad4b4557 · outbound

This paper cites Don’t Use Large Mini- batches, Use Local SGD,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Don’t Use Large Mini- batches, Use Local SGD,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.128365Z

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.

Observation 825e23b8-9c83-4452-9509-a07d4a103aca · outbound

This paper cites QSFL: Two-Level Communication-Efficient Federated Learning on Mobile Edge Devices,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems QSFL: Two-Level Communication-Efficient Federated Learning on Mobile Edge Devices,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.108706Z

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.

Observation 1c988741-631a-4b38-87ee-8ddcd667942e · outbound

This paper cites Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learning,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learning,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.087306Z

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.

Observation 9184b8a4-597c-4599-8267-b85f456163e6 · outbound

This paper cites Federated-learning-based Client Scheduling for Low-latency Wireless Communications,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Federated-learning-based Client Scheduling for Low-latency Wireless Communications,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:21.064738Z

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.

Observation 63d92231-30dd-4112-882f-782f1292fde7 · outbound

This paper cites Horus: Interference-aware and Prediction-based Scheduling in Deep Learning Systems,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Horus: Interference-aware and Prediction-based Scheduling in Deep Learning Systems,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:20.971770Z

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.

Observation 076c19a0-2d98-4737-aa59-8c5457036e78 · outbound

This paper cites Pipeline Network Simulation Calculation based on Improved Newton Jacobian Iterative Method,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Pipeline Network Simulation Calculation based on Improved Newton Jacobian Iterative Method,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:20.778573Z

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.

Observation 7e618437-7037-4f17-bd63-104329a02ba0 · outbound

This paper cites On Nonlinear Fractional Programming,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems On Nonlinear Fractional Programming,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:20.615924Z

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.

Observation fa6987be-2ca3-40be-8e79-c3058720a8d0 · outbound

This paper cites A Reformulation-linearization Method for the Global Optimization of Large-scale Mixed-Integer Linear Fractional Programming Problems and Cyclic Scheduling aApplication,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems A Reformulation-linearization Method for the Global Optimization of Large-scale Mixed-Integer Linear Fractional Programming Problems and Cyclic Scheduling aApplication,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:20.533766Z

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.

Observation 018b6a45-9d0a-40dc-8d7c-792363b98109 · outbound

This paper cites Extensions of Dinkelbach’s Algorithm for Solving Non-linear Fractional Programming Problems,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Extensions of Dinkelbach’s Algorithm for Solving Non-linear Fractional Programming Problems,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:20.522256Z

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.

Observation 0fb3fcda-f97e-4fdd-9565-ce6df27b30e3 · outbound

This paper cites Convergence of A Block Coordinate Descent Method for Nondifferentiable Minimization,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Convergence of A Block Coordinate Descent Method for Nondifferentiable Minimization,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:20.470069Z

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Observation 345f2973-322e-49e9-8306-566eac609b35 · outbound

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

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Learning Multiple Layers of Features From Tiny Images,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:20.271062Z

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

Observation d933272e-73e0-41a5-8ad2-2608802ccc68 · outbound

This paper cites Broadband analog aggregation for low-latency federated edge learning,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Broadband analog aggregation for low-latency federated edge learning,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:20.055919Z

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Observation f750c997-777d-4e79-b488-11c851a75ac7 · outbound

This paper cites Energy Efficient Federated Learning over Wireless Communication Networks,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Energy Efficient Federated Learning over Wireless Communication Networks,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:19.839516Z

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Observation cb0dfa43-3bfa-4def-a182-54d31f89add2 · outbound

This paper cites Very Deep Convolutional Networks for Large-scale Image Recognition,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Very Deep Convolutional Networks for Large-scale Image Recognition,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:19.630693Z

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.

Observation 67245bb7-d599-4c7e-a4c2-556ea1c88826 · outbound

This paper cites Deep Residual Learning for Image Recognition,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems Deep Residual Learning for Image Recognition,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:19.431604Z

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.

Observation a6c6ab4e-da2b-4159-98e3-38d0ec628d5c · outbound

This paper cites CoopFL: Accelerating Federated Learning with DNN Partitioning and Offloading in Hetero- geneous Edge Computing,.

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems CoopFL: Accelerating Federated Learning with DNN Partitioning and Offloading in Hetero- geneous Edge Computing,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:19:19.215331Z

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.

Pith citing papers

Observation 770054e8-dd72-41c5-9768-d654af0509f2 · inbound

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation cites this paper.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T19:24:39.944675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcba5111-ef59-45a3-a02a-956e155fd767 · inbound

PHandover: Parallel Handover in Mobile Satellite Network cites this paper.

PHandover: Parallel Handover in Mobile Satellite Network HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T18:45:38.778439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d6f9294-8b20-4688-862d-7000b3d70693 · inbound

RRTO: A High-Performance Transparent Offloading System for Model Inference in Mobile Edge Computing cites this paper.

RRTO: A High-Performance Transparent Offloading System for Model Inference in Mobile Edge Computing HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T12:30:26.234842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c06dbd26-60a5-42e0-ab7e-5ba5fd6845fb · inbound

Optimizing Split Federated Learning with Unstable Client Participation cites this paper.

Optimizing Split Federated Learning with Unstable Client Participation HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-18T15:26:33.745801Z

Source-reported events for the cited work

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