HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning | Paper Citation Record

Observation fd8775ef-e4fe-4980-a235-f9c62646cc93 · outbound

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

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Split Learning Over Wireless Networks: Parallel Design and Resource Management,

Reference 1

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Observation 3c6f13de-2f8d-4554-9a41-d0fd62f546af · outbound

This paper cites Joint Client Selection and Model Compression for Eﬀicient FL in UA V-Assisted Wireless Networks,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Joint Client Selection and Model Compression for Eﬀicient FL in UA V-Assisted Wireless Networks,

Reference 2

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Observation a95a90bf-0a4c-4eef-a88d-b4c3ae783aec · outbound

This paper cites Adaptive Training and Aggregation for Federated Learning in Multi-Tier Computing Networks,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Adaptive Training and Aggregation for Federated Learning in Multi-Tier Computing Networks,

Reference 3

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Observation febb864d-e923-4193-b407-aa55c041113a · outbound

This paper cites GH- PFL: Advancing Personalized Edge-Based Learning Through Optimized Bandwidth Utilization,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning GH- PFL: Advancing Personalized Edge-Based Learning Through Optimized Bandwidth Utilization,

Reference 4

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Observation ea158d18-bee9-4af2-86c7-de6d12215ec6 · outbound

This paper cites HierFedML: Aggregator Placement and UE Assignment for Hierarchical Federated Learning in Mobile Edge Computing,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning HierFedML: Aggregator Placement and UE Assignment for Hierarchical Federated Learning in Mobile Edge Computing,

Reference 5

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This paper cites HFL-TranWGAN: Knowledge-Driven Cross-Domain Collaborative Anomaly Detec- tion for End-to-End Network Slicing,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning HFL-TranWGAN: Knowledge-Driven Cross-Domain Collaborative Anomaly Detec- tion for End-to-End Network Slicing,

Reference 6

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Observation c77bf2a4-57dd-4669-ae9d-10a09b102ad7 · outbound

This paper cites Device Scheduling and Assignment in Hierarchical Federated Learning for Internet of Things,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Device Scheduling and Assignment in Hierarchical Federated Learning for Internet of Things,

Reference 7

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Observation 9077035c-4677-4f25-8489-8e36d7fafa3b · outbound

This paper cites Model-Oriented Training With Two-Stage Hierarchical Knowledge Distillation Under Non-IID Conditions in Federated Edge–Cloud Collabora- tion,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Model-Oriented Training With Two-Stage Hierarchical Knowledge Distillation Under Non-IID Conditions in Federated Edge–Cloud Collabora- tion,

Reference 8

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Observation ce440ee1-0335-41c3-9395-39cab780f425 · outbound

This paper cites Mobility Accelerates Learning: Convergence Analysis on Hierar- chical Federated Learning in Vehicular Networks,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Mobility Accelerates Learning: Convergence Analysis on Hierar- chical Federated Learning in Vehicular Networks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:34:52.622261Z

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Observation b309b43f-4bcf-4365-b54f-73a593cba1aa · outbound

This paper cites Adaptive Model Pruning for Hierarchical Wireless Federated Learning,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Adaptive Model Pruning for Hierarchical Wireless Federated Learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:34:52.608152Z

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Observation e8930dfc-5fc6-4643-a8b4-6c22fd2c4260 · outbound

This paper cites MOB-FL: Mobility-Aware Federated Learning for Intelligent Connected Vehicles,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning MOB-FL: Mobility-Aware Federated Learning for Intelligent Connected Vehicles,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:34:52.587818Z

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Observation b95d7ae3-9f60-4eb5-81ce-4dcfedac82b9 · outbound

This paper cites Distributed Deep Reinforcement Learning-Based Gradient Quantization for Federated Learning Enabled Vehicle Edge Computing,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Distributed Deep Reinforcement Learning-Based Gradient Quantization for Federated Learning Enabled Vehicle Edge Computing,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:34:52.567920Z

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This paper cites Eﬀicient Vehicle Selec- tion and Resource Allocation for Knowledge Distillation-Based Federated Learning in UA V-Assisted VEC,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Eﬀicient Vehicle Selec- tion and Resource Allocation for Knowledge Distillation-Based Federated Learning in UA V-Assisted VEC,

Reference 13

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Observation 91ec02eb-ec38-43f9-9dbe-0f9f66311fbc · outbound

This paper cites FedICT: Federated Multi-Task Distillation for Multi-Access Edge Computing,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning FedICT: Federated Multi-Task Distillation for Multi-Access Edge Computing,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:34:52.536411Z

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Observation fde333ac-3fb9-45a1-abdb-1feaa3fb44e1 · outbound

This paper cites Asynchronous Multi-Model Dynamic Federated Learning Over Wireless Net- works: Theory, Modeling, and Optimization,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Asynchronous Multi-Model Dynamic Federated Learning Over Wireless Net- works: Theory, Modeling, and Optimization,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:34:52.519125Z

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Observation b9268390-961a-40bb-8a98-34a41651df10 · outbound

This paper cites Communication-Eﬀicient Federated Multi- task Learning Over Wireless Networks,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Communication-Eﬀicient Federated Multi- task Learning Over Wireless Networks,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:34:52.499686Z

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Observation 35ecba06-10cd-4051-9049-c622ac33e1ea · outbound

This paper cites Matching Game for Multi-Task Federated Learning in Internet of Vehicles,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Matching Game for Multi-Task Federated Learning in Internet of Vehicles,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:34:52.482738Z

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This paper cites Adaptive and Parallel Split Federated Learning in Vehicular Edge Computing,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Adaptive and Parallel Split Federated Learning in Vehicular Edge Computing,

Reference 18

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This paper cites Joint Participant Selection and Learning Scheduling for Multi-Model Federated Edge Learning,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Joint Participant Selection and Learning Scheduling for Multi-Model Federated Edge Learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:34:52.437964Z

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Observation 6fcaa05f-a099-47cb-b314-0ee912c2db86 · outbound

This paper cites Mobility-Aware Multi-Task Decentralized Federated Learning for Vehicular Networks: Modeling, Analysis, and Optimization.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Mobility-Aware Multi-Task Decentralized Federated Learning for Vehicular Networks: Modeling, Analysis, and Optimization

Reference 20

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This paper cites Many-Task Federated Fine-Tuning via Unified Task Vectors.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Many-Task Federated Fine-Tuning via Unified Task Vectors

Reference 21

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Observation e6ce971c-c022-4af3-b7b4-9dae3466f5a8 · outbound

This paper cites FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training

Reference 22

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This paper cites Task Selection and Resource Optimization in Multi-Task Federated Learning With Model Decomposition,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Task Selection and Resource Optimization in Multi-Task Federated Learning With Model Decomposition,

Reference 23

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Observation 84b24768-1f18-447d-8fb4-5d83d52bee7b · outbound

This paper cites Entropy and Mobility-Based Model Assignment for Multi-Model Vehicular Federated Learning,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Entropy and Mobility-Based Model Assignment for Multi-Model Vehicular Federated Learning,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:34:52.408600Z

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This paper cites HiFlash: Communication-Eﬀicient Hierarchical Federated Learning With Adaptive Staleness Control and Heterogeneity- Aware Client-Edge Association,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning HiFlash: Communication-Eﬀicient Hierarchical Federated Learning With Adaptive Staleness Control and Heterogeneity- Aware Client-Edge Association,

Reference 25

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This paper cites Fed- Fetch: Faster Federated Learning with Adaptive Downstream Prefetching,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Fed- Fetch: Faster Federated Learning with Adaptive Downstream Prefetching,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:34:52.378427Z

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This paper cites Optimizing Asynchronous Federated Learning: A Delicate Trade-Off Be- tween Model-Parameter Staleness and Update Frequency,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Optimizing Asynchronous Federated Learning: A Delicate Trade-Off Be- tween Model-Parameter Staleness and Update Frequency,

Reference 27

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This paper cites HFEL: Joint edge association and resource allocation for cost-eﬀicient hierar- chical federated edge learning,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning HFEL: Joint edge association and resource allocation for cost-eﬀicient hierar- chical federated edge learning,

Reference 28

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This paper cites Joint Optimization of Platoon Control and Resource Scheduling in Cooperative Vehicle-Infrastructure System,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Joint Optimization of Platoon Control and Resource Scheduling in Cooperative Vehicle-Infrastructure System,

Reference 29

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This paper cites Joint Optimiza- tion of Completion Ratio and Latency of Offloaded Tasks With Multiple Priority Levels in 5G Edge,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Joint Optimiza- tion of Completion Ratio and Latency of Offloaded Tasks With Multiple Priority Levels in 5G Edge,

Reference 30

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This paper cites Dynamic Stochastic Reorientation Particle Swarm Optimization for Adaptive Latent Factor Analysis in High-Dimensional Sparse Matrices,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Dynamic Stochastic Reorientation Particle Swarm Optimization for Adaptive Latent Factor Analysis in High-Dimensional Sparse Matrices,

Reference 31

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This paper cites UA V Swarm-Assisted Two-Tier Hierarchical Federated Learn- ing,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning UA V Swarm-Assisted Two-Tier Hierarchical Federated Learn- ing,

Reference 32

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This paper cites Optimization of STATCOM PI Controller Parameters Using the Hybrid GA-PSO Algorithm,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Optimization of STATCOM PI Controller Parameters Using the Hybrid GA-PSO Algorithm,

Reference 33

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This paper cites PSO-Algorithm- Assisted Attack-Compensated Control for 2-D Fuzzy Systems Under Cyber Attacks,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning PSO-Algorithm- Assisted Attack-Compensated Control for 2-D Fuzzy Systems Under Cyber Attacks,

Reference 34

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This paper cites GA-MADDPG: A Demand-Aware UA V Network Adaptation Method for Joint Communication and Positioning in Emergency Scenarios,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning GA-MADDPG: A Demand-Aware UA V Network Adaptation Method for Joint Communication and Positioning in Emergency Scenarios,

Reference 35

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This paper cites Accuracy Assessment of Industrial Heritage Mapping Based on GA+BP Neural Networks Forecast,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Accuracy Assessment of Industrial Heritage Mapping Based on GA+BP Neural Networks Forecast,

Reference 36

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

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 37

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This paper cites Deep Residual Learning for Image Recognition.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Deep Residual Learning for Image Recognition

Reference 38

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This paper cites Long Short-term Memory RNN.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Long Short-term Memory RNN

Reference 39

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This paper cites Privacy-Preserving Federated Learning for UA V-Enabled Net- works: Learning-Based Joint Scheduling and Resource Manage- ment,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Privacy-Preserving Federated Learning for UA V-Enabled Net- works: Learning-Based Joint Scheduling and Resource Manage- ment,

Reference 40

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Observation d74e8406-edb8-48cc-9fde-a639f2e0d573 · outbound

This paper cites JHPF A-Net: Joint Head Pose and Facial Action Network for Driver Yawning Detection Across Arbitrary Poses in Videos,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning JHPF A-Net: Joint Head Pose and Facial Action Network for Driver Yawning Detection Across Arbitrary Poses in Videos,

Reference 41

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This paper cites On the optimization of UA V- assisted wireless networks for hierarchical federated learning,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning On the optimization of UA V- assisted wireless networks for hierarchical federated learning,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:34:52.135882Z

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Observation 62ae078d-4c10-4b0f-8277-e0a1fe1d188a · outbound

This paper cites Toward Robust Hierarchical Federated Learning in Internet of Vehicles,.

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning Toward Robust Hierarchical Federated Learning in Internet of Vehicles,

Reference 43

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