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Paper Citation Record · LEDGER

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

As of 11 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2501.09934.

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

pith.paper-citation-record.v1
2501.09934 v3

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:34:51.751753Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

  • verified exact3
  • verified fuzzy36
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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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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raw_fallback, observed 2026-08-10T19:34:52.728932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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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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raw_fallback, observed 2026-08-10T19:34:52.713101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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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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raw_fallback, observed 2026-08-10T19:34:52.697499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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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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raw_fallback, observed 2026-08-10T19:34:52.682898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation a6ec4119-a937-413c-b467-abca63b60364 · outbound

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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raw_fallback, observed 2026-08-10T19:34:52.666699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.430068Z digest=sha256:97a1c85d797be59bb08142695fbe8f1aefa4d227d7aa4833ff616a35de8d899b

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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raw_fallback, observed 2026-08-10T19:34:52.651815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.449221Z digest=sha256:143a880a75a2a6c8c091f640c2215e111cb81d090c9b2d66d3fb5678bd1bbf95

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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raw_fallback, observed 2026-08-10T19:34:52.636487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.483112Z digest=sha256:e906b0fa3c510dcd036221ba1223180e7ffc6526f2223e86ad3635116b562a4d

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

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raw_fallback, observed 2026-08-10T19:34:52.622261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.554883Z digest=sha256:c683fe1740fd939f0e2f1a1a455a3db15259745e2a723b11b3656d6138fc0402

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

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raw_fallback, observed 2026-08-10T19:34:52.608152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.564659Z digest=sha256:3f82185e3da7132961d40573779bbf7c3293b954eb498ba06d2bc3087c8697b8

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

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raw_fallback, observed 2026-08-10T19:34:52.587818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.570701Z digest=sha256:7404e838c98b07a5181c4c4a8900fd3c143ce3947fecf17e1e01b0b073ff48ee

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

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raw_fallback, observed 2026-08-10T19:34:52.567920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.576776Z digest=sha256:e3ca3b8656b29497ff533d73b433fefdb548bc0a39737714594cd8b1672b7184

Observation dfb5bd82-5a0e-46a9-9626-5ee24576ec06 · outbound

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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raw_fallback, observed 2026-08-10T19:34:52.551068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.585241Z digest=sha256:9fd757272b87e9b51d8bd5b6c4218d031056bdc592a70dc901f2141e44037ee9

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
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raw_fallback, observed 2026-08-10T19:34:52.536411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.593029Z digest=sha256:d21f8bc605197e2ea39a4952916b969d094f26e8eae8d67db98a08d4caf0a3f7

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

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raw_fallback, observed 2026-08-10T19:34:52.519125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.598489Z digest=sha256:13a308820551bd6ac277f25392c266388cce97635465d73c4797a498d3c90bdc

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
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raw_fallback, observed 2026-08-10T19:34:52.499686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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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

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raw_fallback, observed 2026-08-10T19:34:52.482738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.609018Z digest=sha256:cd058433506c181e3e59b8f138bebbb80a3a9d7f1076033940f2ad954e94a1dc

Observation fc2dc14c-fc84-490a-ac45-996b716b345c · outbound

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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raw_fallback, observed 2026-08-10T19:34:52.461528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.614207Z digest=sha256:a1a600ba09f8b4d293126d33b6228b4092a21af9ed2bf0c59d798e7185038017

Observation 8e67ce0c-7292-407f-b630-374846fdbee7 · outbound

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

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raw_fallback, observed 2026-08-10T19:34:52.437964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.620032Z digest=sha256:9fc10fa339d0d1fd3c021086a65c337028b5cb271eca097f556f04c0ab8cccf4

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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local_arxiv, observed 2026-08-10T19:34:52.095466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.625329Z digest=sha256:1d2afa451852f3a4394a658bbb37b907eceacc285bdad26c895887d8cd340d96

Observation c6d452ac-b203-46ac-b953-497cfa60c4a1 · outbound

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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verified exact
local_arxiv, observed 2026-08-10T19:34:52.066622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.631819Z digest=sha256:e848afd0774f3bd3713330af70363b9737b8d0b53eacb37c00946f7f82d584a2

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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local_arxiv, observed 2026-08-10T19:34:52.038550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.638082Z digest=sha256:7025e9036225b6b20994fb6afafdc7031785d15f7081824827b2a0019aacfe36

Observation a753afaa-726d-43b4-bd30-40c243647453 · outbound

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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raw_fallback, observed 2026-08-10T19:34:52.422595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.643979Z digest=sha256:d5b3ccc5b348205a3e6f587d4a251cd6c52a9940ecdb8c5db2460229b3047436

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.649375Z digest=sha256:78e7666c4e4ab39a3bb0f3bdc7dd56daeac6e4ea2fb0c2a76b50ca73bab5bd8c

Observation 86046f4d-2592-4401-bb86-251a5d221394 · outbound

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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raw_fallback, observed 2026-08-10T19:34:52.392193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.653995Z digest=sha256:bc17e2faaa2e48cf6caa00944a4ffdbe700e7822942e965892ddaf9af3f75dd6

Observation 024eaca9-c2a7-4969-a128-13681198e050 · outbound

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
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raw_fallback, observed 2026-08-10T19:34:52.378427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.658239Z digest=sha256:3e2aeaa1e7d678a9b0f4ba7558c82c134cede723b49447658d8073d0bed69713

Observation 31e84a62-178e-4828-bf31-60108582a9d7 · outbound

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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unresolved
no resolver link, observed 2026-08-10T19:34:51.663179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:34:51.663179Z digest=sha256:276ed51525cf61f9080ee6ee3bbaa3fa13fbc207d49b7ee6702aea2f0f76c87d

Observation 12ae38aa-39be-4cd5-9010-d86f45a6f7b5 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:34:52.352592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.668699Z digest=sha256:e36b32817347973b4c17882d4f8e3bb7d5088a52799db328b3413a7f977c8d88

Observation 117af864-9a3e-4fa5-adbc-30e9f5ee7851 · outbound

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

Resolution
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raw_fallback, observed 2026-08-10T19:34:52.338063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.673400Z digest=sha256:8ed8718547efb18f2593363400ee6e2d92fe8bf6374a87a4b8930eeb4710d559

Observation 034d6d63-c64a-4768-9365-15b405215231 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:34:52.323436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.677599Z digest=sha256:a6637aa16dbed039d8fca8d985df0976f16977164d5d0b003fe6dc3e3f0fe333

Observation 71fd1be7-5129-4a78-8b51-e726aa7f9606 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:34:52.304929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.682271Z digest=sha256:caf19d9329867b8ecd189c1ed3647bf984eee7c43977c1baa206af954dbe32ed

Observation e8a13b48-1157-4d4f-b225-c2e6c8a5f99f · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:34:52.272500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.687864Z digest=sha256:512e1b60541d4a18c01bf48d90c82b0e7b7016a072567b36b8b0b44db5e77659

Observation 35e901de-6971-4276-9866-64bd5b986f1e · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:34:52.256654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.692993Z digest=sha256:da3491ed3960461a8ae9a88993b2618c60fe324255db9a6e52dc697b75498457

Observation 5b03af20-5c93-4528-b488-a219a77edfa6 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:34:52.239948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.698089Z digest=sha256:ef7549c7799d0a0647c9ba828f9a713b047b7aedc005cbe78e228c9e4eb2fe2b

Observation 2de46f88-08ef-45a1-abeb-544de5400a0b · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:34:52.219452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.703541Z digest=sha256:c467db9b6fc81cd2fd6d710498b501ebcfc779693117379945f992f2c18e8f72

Observation d5690ad1-bc08-47bc-b773-df2de6284389 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:34:52.194216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.712641Z digest=sha256:08662c30f5207aa35a7935af505eb484f5b672e84e536a719df2c4863bafe8ac

Observation 6e00e707-cf7d-4956-8341-989a509e4f31 · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-10T19:34:51.718178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:34:51.718178Z digest=sha256:81ca89b95f7a65250107948c33ac07697484d627e553b319b9eb295e80a845ee

Observation eb3a05bd-1b64-449e-93ed-746e13acc6bc · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-10T19:34:51.725455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:34:51.725455Z digest=sha256:5c4dedc938ce256d52aae7ee0ba251d82d61bd328ef7653f28d549da301192ac

Observation d44f3cc0-2730-438a-87da-47ac7b2aba72 · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-10T19:34:51.730811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:34:51.730811Z digest=sha256:88560b30e0b04acff0b664da88f0b8b99e2fceede17705e264b09f56fead6b5a

Observation 63d355fd-8971-4a7b-92e9-20baf313f0a4 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:34:52.177612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.736136Z digest=sha256:a8a0e0664ea53c25b0de4724eb5051d43facf67757f29ad1e4cb16ad619e1303

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:34:52.159830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.742188Z digest=sha256:7de28624dde429d8779d2777aee4308e2352db62db686bc6786b8457a0a45968

Observation 70772355-969e-40a8-8212-b080720f712c · outbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.746985Z digest=sha256:691e62e735cebe61f94e80a0143d5ee2bc50b224e8a737d62ea10594b8492e4f

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:34:52.115507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T19:34:51.751753Z digest=sha256:73b7b1133957c2e618b75dfa97b8db9fd159dd601d1448d0859781bb2c2cc3bc

Pith citing papers

No inbound Pith citation observations are available.