Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T11:55:31.884037Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 1 inbound Pith citation observation for arXiv:2507.22330.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T11:55:31.884037Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
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A source-named dated measurement, never combined with another source.
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83 of 83 outbound references displayed
External citation measurements
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Observation 4b063edb-ccd2-4c81-80a0-14d4edd48c66 · outbound
Hypernetworks for Model-Heterogeneous Personalized Federated Learning Adaptive segmentation enhanced asynchronous federated learning for sustainable intelligent transportation systems
Reference 1
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Observation f18b426d-dc16-4908-8d4b-65baafff07d7 · outbound
Hypernetworks for Model-Heterogeneous Personalized Federated Learning Ai- empowered trajectory anomaly detection for intelligent transportation systems: A hierarchi- cal federated learning approach
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Hypernetworks for Model-Heterogeneous Personalized Federated Learning Harmony: Heterogeneous multi-modal federated learning through disentangled model training
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Observation 91521372-1a29-4780-aa14-0e890f84ee6b · outbound
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Hypernetworks for Model-Heterogeneous Personalized Federated Learning Adaptive Personalized Federated Learning
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Hypernetworks for Model-Heterogeneous Personalized Federated Learning Tifl: A tier-based federated learning system
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Observation 6a34ea21-ed43-481d-9b54-1635f6179fa6 · outbound
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Observation e499e0b6-db8d-4568-8b6d-0aa54bd900ad · outbound
Hypernetworks for Model-Heterogeneous Personalized Federated Learning Expanding the Reach of Federated Learning by Reducing Client Resource Requirements
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Hypernetworks for Model-Heterogeneous Personalized Federated Learning Group knowledge transfer: federated learning of large cnns at the edge
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Observation 3c99636d-8b69-4e04-8034-483214cfe66b · outbound
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Observation 6f34ab4d-08ec-477f-8750-e88a23b6f1fc · outbound
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Hypernetworks for Model-Heterogeneous Personalized Federated Learning Fedrolex: Model-heterogeneous federated learning with rolling sub-model extraction
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Observation bc682e3a-cf60-40d8-829b-7b845a60550c · outbound
Hypernetworks for Model-Heterogeneous Personalized Federated Learning Dfrd: Data-free robustness distillation for heterogeneous federated learning
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Observation fc368276-aeb6-4211-9c3b-c3097e86208a · outbound
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Observation 756a3459-c8be-44aa-ab12-12a0320a8a39 · outbound
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Observation a0802a3a-5595-4bc0-b39e-0efbafdf33f2 · outbound
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Observation 2f8e9fa9-10f6-4c6c-ac14-42db944fc737 · outbound
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Observation 245e328d-f7d2-4cb1-8f44-15b473b171e3 · outbound
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Reference 77
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Observation 6c0e9a66-41de-427d-8538-7325e02c87ec · outbound
Hypernetworks for Model-Heterogeneous Personalized Federated Learning Wide Residual Networks
Reference 78
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Observation c610f713-64db-4dad-bd15-0d9f2e526030 · outbound
Hypernetworks for Model-Heterogeneous Personalized Federated Learning Communication-efficient learning of deep networks from decentralized data
Reference 79
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Observation 26ce51fe-6a55-46a2-856d-ea4ab42afa56 · outbound
Hypernetworks for Model-Heterogeneous Personalized Federated Learning Adam: A Method for Stochastic Optimization
Reference 80
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Observation e4956ecc-63d0-4485-a339-9d7f066771e9 · outbound
Hypernetworks for Model-Heterogeneous Personalized Federated Learning SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
Reference 81
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Observation 8b6b1013-0c0b-4f4f-8733-ef2009a49fbb · outbound
Hypernetworks for Model-Heterogeneous Personalized Federated Learning iDLG: Improved Deep Leakage from Gradients
Reference 82
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Observation c5df9a32-d8a0-4e58-b396-9dd87d243f66 · outbound
Hypernetworks for Model-Heterogeneous Personalized Federated Learning Unresolved cited work
Reference 2023
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Observation bddbfad0-5c0c-4a79-80ef-f73c8c12feba · inbound
MOSAIC: Orchestrating Collaborative Knowledge Tracing with Hierarchical Semantic Alignment Hypernetworks for Model-Heterogeneous Personalized Federated Learning
Reference 77
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