GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network | Paper Citation Record

Observation a88d9632-5689-4918-b032-a6459d9ea08f · outbound

This paper cites Secure and traceable multikey image retrieval in cloud-assisted internet of things.IEEE Internet of Things Journal, pages 1–1, 2024.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Secure and traceable multikey image retrieval in cloud-assisted internet of things.IEEE Internet of Things Journal, pages 1–1, 2024

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.758382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d2440950-50e5-4ba4-9219-ebab1a0659c7 · outbound

This paper cites Alqahtani,andMinChen.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Alqahtani,andMinChen

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.746821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9f36a806-b54a-44ca-8188-5547ef8c64cf · outbound

This paper cites Enabling balanced data deduplication in mobile edge computing.IEEE Trans- actionsonParallelandDistributedSystems ,34(5):1420–1431,2023.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Enabling balanced data deduplication in mobile edge computing.IEEE Trans- actionsonParallelandDistributedSystems ,34(5):1420–1431,2023

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.734590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 57ec1fa9-cee7-4e55-87e1-b299da7b824e · outbound

This paper cites Ripple: Enabling decentralized data deduplication at the edge.IEEE Transactions on Parallel and Distributed Systems, 2024.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Ripple: Enabling decentralized data deduplication at the edge.IEEE Transactions on Parallel and Distributed Systems, 2024

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.721571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9e97b775-a803-4235-bfa5-bf2811995dc3 · outbound

This paper cites Edge data deduplication under uncertainties: A robust optimization approach.IEEE Transactions on Parallel and Distributed Systems, 2024.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Edge data deduplication under uncertainties: A robust optimization approach.IEEE Transactions on Parallel and Distributed Systems, 2024

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.708932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ad659637-a763-4126-8aad-6f43afad5a9e · outbound

This paper cites Influence maximization on social graphs: A survey.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Influence maximization on social graphs: A survey

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.694784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 74e8424a-95a3-40cb-8381-a51adb46e32c · outbound

This paper cites IEEETransactions on Vehicular Technology, pages 1–16, 2023.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network IEEETransactions on Vehicular Technology, pages 1–16, 2023

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.680449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 070b48c1-bac0-42f8-ba4c-48e02fd258d3 · outbound

This paper cites Evit: Privacy-preserving image retrieval via encrypted vision transformer in cloud computing.IEEE Transactions on Circuits and Systems for Video Technology, 34(8):7467–7483, 2024.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Evit: Privacy-preserving image retrieval via encrypted vision transformer in cloud computing.IEEE Transactions on Circuits and Systems for Video Technology, 34(8):7467–7483, 2024

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.669100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7a1c2824-6530-4e4d-9afe-5233ab41aa48 · outbound

This paper cites Novel transformation deep learning model for electrocardio- gram classification and arrhythmia detection using edge computing.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Novel transformation deep learning model for electrocardio- gram classification and arrhythmia detection using edge computing

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.657739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e39cd530-17e7-498c-9ae5-3ced334e1bb4 · outbound

This paper cites Real-time monitoring and analysisoftrackandfieldathletesbasedonedgecomputinganddeep reinforcement learning algorithm.Alexandria Engineering Journal, 114:136–146, 2025.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Real-time monitoring and analysisoftrackandfieldathletesbasedonedgecomputinganddeep reinforcement learning algorithm.Alexandria Engineering Journal, 114:136–146, 2025

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.646125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 07713c3f-91de-4b46-b856-3a25ed151a59 · outbound

This paper cites Agricultural weed identification in images and videos by integrating optimized deep learning architecture on an edge computing technology.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Agricultural weed identification in images and videos by integrating optimized deep learning architecture on an edge computing technology

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.633285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c8692869-c66a-4b83-83aa-5ce9184a14b6 · outbound

This paper cites Pflow: An end-to-end heterogeneous acceleration frame- work for cnn inference on fpgas.Journal of Systems Architecture, 150:103113, 2024.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Pflow: An end-to-end heterogeneous acceleration frame- work for cnn inference on fpgas.Journal of Systems Architecture, 150:103113, 2024

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.622917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e2557e18-9799-4c4b-8efd-04f078dab08e · outbound

This paper cites Asurveyofvideo surveillance systems in smart city.Electronics, 12(17):3567, 2023.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Asurveyofvideo surveillance systems in smart city.Electronics, 12(17):3567, 2023

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.612564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dee236d7-43e9-4d7f-831e-b98f2e43a552 · outbound

This paper cites mm-casgan: A cascaded adversarial neural framework for mmwave radar point cloud enhancement.Information Fusion, 108:102388, 2024.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network mm-casgan: A cascaded adversarial neural framework for mmwave radar point cloud enhancement.Information Fusion, 108:102388, 2024

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.600767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b3e290c8-4b11-4889-b9c9-23d669ca6a6a · outbound

This paper cites Cool: a conjoint perspective on spatio-temporal graph neural network for traffic fore- casting.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Cool: a conjoint perspective on spatio-temporal graph neural network for traffic fore- casting

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.588736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ebaadd64-86c7-4ff1-aeb1-2724f3a3d72a · outbound

This paper cites Eeoa: cost and energy efficient task scheduling in a cloud-fog framework.Sensors, 23(5):2445, 2023.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Eeoa: cost and energy efficient task scheduling in a cloud-fog framework.Sensors, 23(5):2445, 2023

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.576818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 66b11a2d-d8c7-4065-9a80-78a6c9b00fa0 · outbound

This paper cites A cost and energy efficient taskschedulingtechniquetooffloadmicroservicesbasedapplications in mobile cloud computing.IEEE Access, 10:46633–46651, 2022.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network A cost and energy efficient taskschedulingtechniquetooffloadmicroservicesbasedapplications in mobile cloud computing.IEEE Access, 10:46633–46651, 2022

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.565334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 75d78c8b-f4a8-4322-9316-5b9a72ceb12f · outbound

This paper cites Adaptive compression offloading and resource allocationforedgevisioncomputing.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Adaptive compression offloading and resource allocationforedgevisioncomputing

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.553971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4a521c76-bd90-429f-ab0e-2bee20a7bc9f · outbound

This paper cites Deep reinforcement learning for trajectory path planning and distributed inference in resource- constrained uav swarms.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Deep reinforcement learning for trajectory path planning and distributed inference in resource- constrained uav swarms

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.542520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7704b182-6508-4d67-b8c7-e508b45c2bf5 · outbound

This paper cites Joint multi-domain resource allocation and trajectory optimization in uav-assistedmaritimeiotnetworks.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Joint multi-domain resource allocation and trajectory optimization in uav-assistedmaritimeiotnetworks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.530896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0cfd8c66-ba9c-45ce-a303-6f66a0cb7570 · outbound

This paper cites Digital twin-assisted urllc-enabled task offloading in mobile edge network via robust combinatorial optimization.IEEE Journal on Selected Areas in Communications, 2023.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Digital twin-assisted urllc-enabled task offloading in mobile edge network via robust combinatorial optimization.IEEE Journal on Selected Areas in Communications, 2023

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.517859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8ee45195-46e8-430e-a40f-783ef16748a8 · outbound

This paper cites Joint sensing adaptation and model placement in 6g fabric computing.IEEE Journal on Selected Areas in Communications, 41(7):2013–2024, 2023.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Joint sensing adaptation and model placement in 6g fabric computing.IEEE Journal on Selected Areas in Communications, 41(7):2013–2024, 2023

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.506421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 09ecefe2-6284-4096-abc4-fe7be48d34d7 · outbound

This paper cites Collaborative computation offloading and resource allocation in multi-uav-assisted iotnetworks:Adeepreinforcementlearningapproach.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Collaborative computation offloading and resource allocation in multi-uav-assisted iotnetworks:Adeepreinforcementlearningapproach

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.493460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3c2b3a1f-baa9-4457-95e9-3a5c59f842c1 · outbound

This paper cites Jointuavtrajectoryplanning,dagtaskschedul- ing, andservice functiondeployment basedon drlin uav-empowered edge computing.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Jointuavtrajectoryplanning,dagtaskschedul- ing, andservice functiondeployment basedon drlin uav-empowered edge computing

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.482458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 04904765-edc5-4e9e-a467-d4fd768c0ae4 · outbound

This paper cites Sgpl: An intelligent game-based secure collab- orative communication scheme for metaverse over 5g and beyond networks.IEEEJournalonSelectedAreasinCommunications ,2023.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Sgpl: An intelligent game-based secure collab- orative communication scheme for metaverse over 5g and beyond networks.IEEEJournalonSelectedAreasinCommunications ,2023

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.470955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fa3b59bf-225e-4364-a9aa-624bfc4a3dea · outbound

This paper cites Model-assistedmulti-source fusion hypergraph convolutional neural networks for intelligent few- shot fault diagnosis to electro-hydrostatic actuator.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Model-assistedmulti-source fusion hypergraph convolutional neural networks for intelligent few- shot fault diagnosis to electro-hydrostatic actuator

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.460329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3bcc7a88-9b4a-47bb-8525-ef45a35b17fd · outbound

This paper cites Enhancement of traffic forecasting through graph neural network-based information fusion techniques.Information Fusion, 110:102466, 2024.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Enhancement of traffic forecasting through graph neural network-based information fusion techniques.Information Fusion, 110:102466, 2024

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.449040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fe84f824-898b-4062-874b-04a384595f3e · outbound

This paper cites Neural network operators: constructive interpola- tion of multivariate functions.Neural Networks, 67:28–36, 2015.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Neural network operators: constructive interpola- tion of multivariate functions.Neural Networks, 67:28–36, 2015

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.438051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 985b46c6-b27f-4f77-8c0e-415bd7cf3a4a · outbound

This paper cites Spectral Networks and Locally Connected Networks on Graphs.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Spectral Networks and Locally Connected Networks on Graphs

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T11:21:50.881599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a044bc8a-352d-422b-9286-128eb4083595 · outbound

This paper cites Inductive repre- sentation learning on large graphs.Advances in Neural Information Processing Systems, 30, 2017.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Inductive repre- sentation learning on large graphs.Advances in Neural Information Processing Systems, 30, 2017

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.426248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7fd3412b-67cf-4f3b-9709-3d799a7664ce · outbound

This paper cites Spatio- temporalfusiongraphconvolutionalnetworkfortrafficflowforecast- ing.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Spatio- temporalfusiongraphconvolutionalnetworkfortrafficflowforecast- ing

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.412502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7bd91d45-542b-4dea-9d5a-9931d4791d1d · outbound

This paper cites Fograph:Enablingreal-timedeepgraphinferencewithfog computing.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Fograph:Enablingreal-timedeepgraphinferencewithfog computing

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.398957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7ed991a0-b046-4a14-bbe2-570c327dbc80 · outbound

This paper cites FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T11:21:50.905754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a046e49-c1a7-4a89-bec7-1bfa6bac675e · outbound

This paper cites Reducing com- munication in graph neural network training.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Reducing com- munication in graph neural network training

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.385934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8d7093a9-af7e-4f8b-9402-53effb789dd6 · outbound

This paper cites Distdgl: distributed graph neural network training for billion-scale graphs.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Distdgl: distributed graph neural network training for billion-scale graphs

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.370260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d97dbf09-c4e2-4292-8371-272d9639f79f · outbound

This paper cites Gnn at the edge: Cost-efficient graph neural network processing over distributed edge servers.IEEE Journal on Selected Areas in Communications, 41(3):720–739, 2022.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Gnn at the edge: Cost-efficient graph neural network processing over distributed edge servers.IEEE Journal on Selected Areas in Communications, 41(3):720–739, 2022

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.355198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7a662844-089d-448c-bc28-e34373e398d6 · outbound

This paper cites Intelligent offloading and resource allocation in heteroge- neous aerial access iot networks.IEEE Internet of Things Journal, 10(7):5704–5718, 2022.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Intelligent offloading and resource allocation in heteroge- neous aerial access iot networks.IEEE Internet of Things Journal, 10(7):5704–5718, 2022

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.334021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a9412e00-340a-4e13-9b2b-b8a103a97625 · outbound

This paper cites Multi-agent reinforcement learn- ing based resource management in mec-and uav-assisted vehicular networks.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Multi-agent reinforcement learn- ing based resource management in mec-and uav-assisted vehicular networks

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.314366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7dedc3a8-0084-45a2-ab9c-b1b42413c995 · outbound

This paper cites Graph-reinforcement- learning-basedtaskoffloadingformultiaccessedgecomputing.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Graph-reinforcement- learning-basedtaskoffloadingformultiaccessedgecomputing

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.290086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 92da0b73-7fa8-4246-930c-09eb1fe20472 · outbound

This paper cites Exploring graph neural networks for joint cruise control and task offloading in uav-enabled mobile edge computing.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Exploring graph neural networks for joint cruise control and task offloading in uav-enabled mobile edge computing

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.278272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b53dd70c-8aee-4966-bd01-bc3f9104c9ff · outbound

This paper cites Dynamic semantic compression for cnn inference in multi-access edge computing: A graph reinforcement learning-based autoencoder.IEEE Transactions on Wireless Communications, 2024.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Dynamic semantic compression for cnn inference in multi-access edge computing: A graph reinforcement learning-based autoencoder.IEEE Transactions on Wireless Communications, 2024

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.264399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fa9b852c-3242-470a-8c7d-d3b2c4a0b8b6 · outbound

This paper cites Dependenttaskoffloadinginedgecomputingusinggnn and deep reinforcement learning.IEEE Internet of Things Journal, 2024.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Dependenttaskoffloadinginedgecomputingusinggnn and deep reinforcement learning.IEEE Internet of Things Journal, 2024

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.248433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d5141e09-8607-49b5-aec0-c05d17ece744 · outbound

This paper cites an unresolved cited work.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:21:51.231574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9599eef1-06bd-4192-8022-c073764cac6b · outbound

This paper cites Designing multithreaded algorithms for breadth-first search and st-connectivity on the cray mta-2.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Designing multithreaded algorithms for breadth-first search and st-connectivity on the cray mta-2

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.214699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 97240139-06ff-4a64-b808-845ce5436efc · outbound

This paper cites Connectivity algorithm with depth first search (dfs) on simple graphs.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Connectivity algorithm with depth first search (dfs) on simple graphs

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.200995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e9a0d611-6e3e-4080-afbb-6c7e10cb7be9 · outbound

This paper cites Multi-agent actor-critic for mixed cooperative- competitive environments.Advances in Neural Information Process- ing Systems, 30, 2017.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Multi-agent actor-critic for mixed cooperative- competitive environments.Advances in Neural Information Process- ing Systems, 30, 2017

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.187805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4d5c6edc-4437-4756-8740-84ba6b1f97c3 · outbound

This paper cites Multistageenergymanagement ofcoordinatedsmartbuildings:Amultiagentmarkovdecisionprocess approach.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Multistageenergymanagement ofcoordinatedsmartbuildings:Amultiagentmarkovdecisionprocess approach

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.175552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2b33e64c-250a-4afe-9c92-2acc8a4c2653 · outbound

This paper cites Data fusion and transfer learning empowered granular trust evaluation for internet of things.Information Fusion, 78:149–157, 2022.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Data fusion and transfer learning empowered granular trust evaluation for internet of things.Information Fusion, 78:149–157, 2022

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.163988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f77f3fc0-6513-4c2a-ab15-114e004777b2 · outbound

This paper cites Fairness- based3-dmulti-uavtrajectoryoptimizationinmulti-uav-assistedmec system.IEEEInternetofThingsJournal ,10(13):11383–11395,2023.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Fairness- based3-dmulti-uavtrajectoryoptimizationinmulti-uav-assistedmec system.IEEEInternetofThingsJournal ,10(13):11383–11395,2023

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.150530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ac8073d2-5b6e-4649-9c9f-3e619ed5c58e · outbound

This paper cites Chatmdg: A discourse parsing graph fusion based approach for multi-party dialogue generation.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Chatmdg: A discourse parsing graph fusion based approach for multi-party dialogue generation

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.135955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5efc8cf0-22af-43fd-acf6-f5da3d344ab3 · outbound

This paper cites Simplifying graph convolutional networks.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Simplifying graph convolutional networks

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.121556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a868b6ab-a1d4-4535-9d5f-b8d52d37661c · outbound

This paper cites Energy– latency tradeoff for computation offloading in uav-assisted multi- access edge computing system.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Energy– latency tradeoff for computation offloading in uav-assisted multi- access edge computing system

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.108547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fc221702-59b6-4d80-9aae-becf4e30c8bd · outbound

This paper cites Revisiting semi-supervised learning with graph embeddings.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Revisiting semi-supervised learning with graph embeddings

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.094024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1632533f-fde4-44d6-92c1-2ac2aa1b4acb · outbound

This paper cites Collective classification in network data.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Collective classification in network data

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:21:51.081570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 58514b93-4309-46db-81db-0ece5e5678dc · outbound

This paper cites Proximal Policy Optimization Algorithms.

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network Proximal Policy Optimization Algorithms

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-16T11:21:50.998953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers