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Paper Citation Record · LEDGER

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models

As of 10 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2507.06449.

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

pith.paper-citation-record.v1
2507.06449 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:11:23.108795Z

measured 32 of 32 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T06:04:18.226700Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T06:04:22.304909Z

Reference resolution

31 of 31 outbound references displayed

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  • verified fuzzy15
  • unresolved14
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External citation measurements

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Outbound references

Observation 66993040-2e66-4a21-9673-ce594e61816d · outbound

This paper cites Denoising diffusion probabilistic models,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Denoising diffusion probabilistic models,

Reference 1

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Observation d211ca8a-41f3-47ad-92bc-f3665c87f482 · outbound

This paper cites Denoising diffusion implicit models,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Denoising diffusion implicit models,

Reference 2

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Observation d4ad6b62-765a-45ee-919f-22c765d1bc43 · outbound

This paper cites Score-based generative modeling through stochastic differential equations,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Score-based generative modeling through stochastic differential equations,

Reference 3

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Observation 2ec76122-a9ed-4334-94a8-9e2115eddb1c · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models High- resolution image synthesis with latent diffusion models,

Reference 4

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Observation f9ca3718-5b3e-4e46-b55f-afc8026e33fe · outbound

This paper cites Diffusion models: A comprehensive survey of methods and applications,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Diffusion models: A comprehensive survey of methods and applications,

Reference 5

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Observation 396cb569-ba8e-4881-9732-ff078d5050df · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Communication-efficient learning of deep networks from decentralized data,

Reference 6

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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 a8969388-64eb-45d1-8970-372af9273cd9 · outbound

This paper cites When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 7

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Observation 8559b80f-cf22-4dab-9d90-715f2be2b0f8 · outbound

This paper cites Federated learning for generalization, robustness, fairness: A survey and benchmark,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Federated learning for generalization, robustness, fairness: A survey and benchmark,

Reference 8

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Observation 7e735da1-2a13-4032-9f57-cf6ca31643db · outbound

This paper cites Feddiff: Diffusion model driven federated learning for multi-modal and multi-clients,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Feddiff: Diffusion model driven federated learning for multi-modal and multi-clients,

Reference 9

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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 746af3ca-530f-470d-af7b-ead0b85deaa3 · outbound

This paper cites Fedst: Federated style transfer learning for non-iid image segmentation,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Fedst: Federated style transfer learning for non-iid image segmentation,

Reference 10

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

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Observation 78337dfc-d3ab-43bf-a266-78defe50e45c · outbound

This paper cites Mitigating Data Heterogeneity in Federated Learning with Data Augmentation.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Mitigating Data Heterogeneity in Federated Learning with Data Augmentation

Reference 11

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

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Observation 8cb41aea-c64e-4a3e-8491-ee87e4e77bfb · outbound

This paper cites Dense: Data-free one-shot federated learning,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Dense: Data-free one-shot federated learning,

Reference 12

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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 b898a7d2-9ac0-4e9b-9f66-ec8abb1d1fb6 · outbound

This paper cites Exploring one-shot semi-supervised federated learning with pre-trained diffusion models,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Exploring one-shot semi-supervised federated learning with pre-trained diffusion models,

Reference 13

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

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Observation 82b93e70-a144-41a9-909e-e9f639f71c6f · outbound

This paper cites Phoenix: A federated generative diffusion model,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Phoenix: A federated generative diffusion model,

Reference 14

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Observation 6d7f10f1-3200-488e-aec8-cf4e60aa6001 · outbound

This paper cites Training Diffusion Models with Federated Learning.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Training Diffusion Models with Federated Learning

Reference 15

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Observation 81014283-c702-441d-a923-618311840cc7 · outbound

This paper cites Federated learning with diffusion models for privacy- sensitive vision tasks,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Federated learning with diffusion models for privacy- sensitive vision tasks,

Reference 16

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

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Observation 7761ea7a-f40e-486f-96a6-f4de3eb5c48b · outbound

This paper cites Federated Learning with Non-IID Data.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Federated Learning with Non-IID Data

Reference 17

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Observation 21860afc-7a31-4311-89a2-1ce62622092e · outbound

This paper cites On the convergence of fedavg on non-iid data,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models On the convergence of fedavg on non-iid data,

Reference 18

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Observation e3c8c323-1e42-40da-9d9e-fe90666fbf70 · outbound

This paper cites Optimizing federated learning on non-iid data with reinforcement learning,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Optimizing federated learning on non-iid data with reinforcement learning,

Reference 19

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Observation 6143bb31-fcec-4c03-8ff7-759d0297b8f9 · outbound

This paper cites A communication-efficient hierarchical federated learning framework via shaping data distribution at edge,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models A communication-efficient hierarchical federated learning framework via shaping data distribution at edge,

Reference 20

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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 3f9d75ce-92f7-4493-bd0c-90e853bc92a8 · outbound

This paper cites Federated optimization in heterogeneous networks,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Federated optimization in heterogeneous networks,

Reference 21

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Observation e6332512-84e9-4850-8598-194ff6b70b4e · outbound

This paper cites Model-contrastive federated learning,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Model-contrastive federated learning,

Reference 22

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

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Observation 807b23a0-b588-4583-81cb-2628de3af1d0 · outbound

This paper cites Scaffold: Stochastic controlled averaging for federated learn- ing,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Scaffold: Stochastic controlled averaging for federated learn- ing,

Reference 23

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Observation e8b1a959-0fe6-46db-9c69-61dc585d99d3 · outbound

This paper cites Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models

Reference 24

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Observation 19c784f3-d433-40ad-bdc2-e394e6c53b89 · outbound

This paper cites Structural pruning for diffusion models,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Structural pruning for diffusion models,

Reference 25

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Observation ba4f0b40-69ad-4ba9-a97a-f24353579e0c · outbound

This paper cites Vector quantized diffusion model for text-to-image synthesis,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Vector quantized diffusion model for text-to-image synthesis,

Reference 26

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

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Observation f65618e3-b4f1-4cb5-8366-99bed829c069 · outbound

This paper cites Post-training quantiza- tion on diffusion models,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Post-training quantiza- tion on diffusion models,

Reference 27

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raw_fallback, observed 2026-08-06T19:11:23.513856Z

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 468cfe62-0ea2-41b7-a42b-021cea4ca09d · outbound

This paper cites Knowledge diffusion for distillation,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Knowledge diffusion for distillation,

Reference 28

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raw_fallback, observed 2026-08-06T19:11:23.492479Z

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 6b5a384a-119a-4e4b-91d7-f93c0bec5653 · outbound

This paper cites Depgraph: Towards any structural pruning,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Depgraph: Towards any structural pruning,

Reference 29

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raw_fallback, observed 2026-08-06T19:11:23.473469Z

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 95177176-a646-4a1a-88d5-0ee39f2c92dc · outbound

This paper cites Sample-level data selection for federated learning,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Sample-level data selection for federated learning,

Reference 30

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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 ebad7c32-8d11-4e5d-86cc-4d793e2b399e · outbound

This paper cites Feddisco: Fed- erated learning with discrepancy-aware collaboration,.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Feddisco: Fed- erated learning with discrepancy-aware collaboration,

Reference 31

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Pith citing papers

Observation 707616bf-6dc9-4f56-a074-f951818c7917 · inbound

Cooperative Perception: A Resource-Efficient Framework for Multi-Drone 3D Scene Reconstruction Using Federated Diffusion and NeRF cites this paper.

Cooperative Perception: A Resource-Efficient Framework for Multi-Drone 3D Scene Reconstruction Using Federated Diffusion and NeRF FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models

Reference 42

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

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