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Paper Citation Record · LEDGER

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations

As of 8 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2608.03436.

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

pith.paper-citation-record.v1
2608.03436 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:13:01.421391Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

25 of 25 outbound references displayed

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  • verified fuzzy15
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8a9f7945-5f14-4ab5-89b7-d16462642c65 · outbound

This paper cites Deepglobe 2018: A challenge to parse the earth through satellite images.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations Deepglobe 2018: A challenge to parse the earth through satellite images

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-05T19:13:04.801874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:12:59.299451Z digest=sha256:eefc30c20390cad668e222c4d6a2349581d7a7e9529feb869d1e4f02867cee7a

Observation c66a0577-4485-42df-85e2-09d92729afd7 · outbound

This paper cites sat-QFL: Secure Quan- tum Federated Learning for Low Orbit Satellites.arXiv preprint arXiv:2509.16504, 2025.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations sat-QFL: Secure Quan- tum Federated Learning for Low Orbit Satellites.arXiv preprint arXiv:2509.16504, 2025

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:12:59.379321Z digest=sha256:667d2dd1f91fba116ef2ede346bf4e421f19c81f6e9f24a44da9522b70948e5f

Observation cd039051-66c1-4219-a22c-f2910bb3183f · outbound

This paper cites Decentralized Trust for Space AI: Blockchain-Based Federated Learning Across Multi-Vendor LEO Satellite Networks.arXiv preprint arXiv:2512.08882, 2025.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations Decentralized Trust for Space AI: Blockchain-Based Federated Learning Across Multi-Vendor LEO Satellite Networks.arXiv preprint arXiv:2512.08882, 2025

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:12:59.450580Z digest=sha256:d7357894149db005bc00415168bbfd60f8161e9814b96ecebb0b566eb712df57

Observation 755df70d-2952-4718-93f8-99e64827bf1a · outbound

This paper cites AsyncFLEO: Asynchronous Federated Learning for LEO Satellite Constellations with High-Altitude Platforms.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations AsyncFLEO: Asynchronous Federated Learning for LEO Satellite Constellations with High-Altitude Platforms

Reference 4

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raw_fallback, observed 2026-08-05T19:13:04.675763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:12:59.539725Z digest=sha256:c8a5cb91b4354c8d33eebf0cff6e8a972ecf97d5aff0d6be7948cbb8dc485cbb

Observation 0626090b-1f73-4233-bc63-9761fb3a5691 · outbound

This paper cites FedHAP: Fast Federated Learning for LEO Constellations Using Col- laborative HAPs.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations FedHAP: Fast Federated Learning for LEO Constellations Using Col- laborative HAPs

Reference 5

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raw_fallback, observed 2026-08-05T19:13:04.531896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5f257284-cd21-4d81-8c56-1f5ec7fd1942 · outbound

This paper cites EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:12:59.686180Z digest=sha256:004ae0f688d1c6419ecd2318a91998b6ea3d0687a829d786d7607d5c32371279

Observation 25401415-ec9c-4310-9e92-780545360f94 · outbound

This paper cites FedFusion: Manifold Driven Federated Learning for Multi-Satellite and Multi-Modality Fusion.IEEE Trans- actions on Geoscience and Remote Sensing, 2023.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations FedFusion: Manifold Driven Federated Learning for Multi-Satellite and Multi-Modality Fusion.IEEE Trans- actions on Geoscience and Remote Sensing, 2023

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:12:59.774467Z digest=sha256:501475a9e212ae7c5ea8ae551008699072ea6c246c24a82cde55323bab82e5a3

Observation 35866cd0-8fe0-45a6-ba3b-5c749f0ea3a0 · outbound

This paper cites HiSatFL: A Hierarchical Federated Learning Framework for Satel- lite Networks with Cross-Domain Privacy Adaptation.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations HiSatFL: A Hierarchical Federated Learning Framework for Satel- lite Networks with Cross-Domain Privacy Adaptation

Reference 8

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raw_fallback, observed 2026-08-05T19:13:04.245536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:12:59.859818Z digest=sha256:68d4812cf7b4db2f1bebf1d5f98f4c9a46a678500536b69d0f6837add297bacb

Observation a16dd7b5-8d22-4a17-95dd-3824bbdc4d85 · outbound

This paper cites FedSN: A Federated Learning Framework over Heterogeneous LEO Satellite Networks.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations FedSN: A Federated Learning Framework over Heterogeneous LEO Satellite Networks

Reference 9

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no resolver link, observed 2026-08-05T19:12:59.954919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:12:59.954919Z digest=sha256:53bb10f74d3f6824b559ab459abeb21f9ce00a2a559827b313b75d8ddb09b916

Observation 3641e118-894a-492e-bb49-f385f70d0f59 · outbound

This paper cites A Semi-Supervised Federated Learning Framework with Hierarchical Clustering Aggregation for Heterogeneous Satellite Networks.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations A Semi-Supervised Federated Learning Framework with Hierarchical Clustering Aggregation for Heterogeneous Satellite Networks

Reference 10

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verified exact
local_arxiv, observed 2026-08-05T19:13:02.232357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7719240e-c2b4-480c-90d3-67c6936f076d · outbound

This paper cites Ground-Assisted Federated Learning in LEO Satellite Constellations.IEEE Wireless Commu- nications Letters, 11(4):717–721, 2022.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations Ground-Assisted Federated Learning in LEO Satellite Constellations.IEEE Wireless Commu- nications Letters, 11(4):717–721, 2022

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-05T19:13:04.101300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 74190661-bb08-4646-884f-6fb9c4f69b70 · outbound

This paper cites Sparse Incremental Aggregation in Satellite Federated Learning.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations Sparse Incremental Aggregation in Satellite Federated Learning

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-05T19:13:02.072718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:13:00.183183Z digest=sha256:05f6bad06f0b372ce73c3c77198e031c561c31df1098c808cededb3ead7bca22

Observation 87921ee9-b6c8-4715-8d8e-98004812d296 · outbound

This paper cites an unresolved cited work.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations Unresolved cited work

Reference 13

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unresolved
raw_fallback, observed 2026-08-05T19:13:03.951697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:13:00.251344Z digest=sha256:da4b82ba336f5666fa1eeb721b0175458146d269efb16e506510b97e1e80b0d5

Observation 3031fbec-1cc6-4ea3-8115-82d17d77cadc · outbound

This paper cites FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations

Reference 14

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unresolved
no resolver link, observed 2026-08-05T19:13:00.330125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:13:00.330125Z digest=sha256:afbb5b0856f705a67a466175aa6914d5563b738202f91090932a275f35d98ba0

Observation 65b577e2-8025-4f84-aaa2-1c38652c4815 · outbound

This paper cites DSFL: Decentralized Satellite Federated Learning for Energy- Aware LEO Constellation Computing.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations DSFL: Decentralized Satellite Federated Learning for Energy- Aware LEO Constellation Computing

Reference 15

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raw_fallback, observed 2026-08-05T19:13:03.806976Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:13:00.415896Z digest=sha256:2d576280a23bc22d8fffaed0a78d1a46331353f22d2efc1a417c38a412e4166c

Observation 00003f5a-061c-4999-9331-d8e9de9faf87 · outbound

This paper cites FedGSM: Efficient Federated Learning for LEO Constellations with Gra- dient Staleness Mitigation.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations FedGSM: Efficient Federated Learning for LEO Constellations with Gra- dient Staleness Mitigation

Reference 16

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5755a876-f00b-444e-a19b-2b5032eb6137 · outbound

This paper cites Multi-Round Decentralized Dataset Distillation with Federated Learning for Low Earth Orbit Satellite Communication.Future Generation Computer Systems, 164:107570, 2025.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations Multi-Round Decentralized Dataset Distillation with Federated Learning for Low Earth Orbit Satellite Communication.Future Generation Computer Systems, 164:107570, 2025

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-05T19:13:03.475275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation dae4e35f-8778-44b2-9439-896e84ad8c91 · outbound

This paper cites RAFL: Reputation-Aware Federated Learning with Hierarchi- cal Aggregation in LEO Satellite Networks.Journal of Systems Architecture, 168:103565, 2025.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations RAFL: Reputation-Aware Federated Learning with Hierarchi- cal Aggregation in LEO Satellite Networks.Journal of Systems Architecture, 168:103565, 2025

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-05T19:13:03.287745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 679790bf-adca-4c82-8502-96b5ba2d08a4 · outbound

This paper cites Connection-Density- Aware Satellite-Ground Federated Learning via Asyn- chronous Dynamic Aggregation.Future Generation Computer Systems, 155:312–323, 2024.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations Connection-Density- Aware Satellite-Ground Federated Learning via Asyn- chronous Dynamic Aggregation.Future Generation Computer Systems, 155:312–323, 2024

Reference 19

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:13:00.730270Z digest=sha256:c11e1ea102b7087ce65c9a88483a92b616df25d1db6f25aa3b1f3a2aa8f5b13d

Observation d6d36221-9d05-4d51-95a7-d393c32a6402 · outbound

This paper cites DFedSat: Communication-Efficient and Robust Decentralized Federated Learning for LEO Satellite Constellations.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations DFedSat: Communication-Efficient and Robust Decentralized Federated Learning for LEO Satellite Constellations

Reference 20

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verified exact
local_arxiv, observed 2026-08-05T19:13:01.850422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:13:00.843681Z digest=sha256:4f90a20896194766300d399f631b049f25438ebefaecc5cbf858a306e2e8cd8f

Observation 65e038e0-6221-457e-94e8-5b07c027b958 · outbound

This paper cites FedLEO: An Offloading-Assisted Decen- tralized Federated Learning Framework for Low Earth Orbit Satellite Networks.IEEE Transactions on Mobile Computing, 2023.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations FedLEO: An Offloading-Assisted Decen- tralized Federated Learning Framework for Low Earth Orbit Satellite Networks.IEEE Transactions on Mobile Computing, 2023

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-05T19:13:02.970672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:13:00.937961Z digest=sha256:b6bd22c690395880b42e5f2a3eeb4e8e6a178117e0e70df3d58f1a643670493c

Observation 0d01647b-b5c0-45ed-856a-52151108327f · outbound

This paper cites FedUR: Fed- erated Learning Optimization through Adaptive Central- ized Learning Optimizers.IEEE Transactions on Signal Processing, 2023.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations FedUR: Fed- erated Learning Optimization through Adaptive Central- ized Learning Optimizers.IEEE Transactions on Signal Processing, 2023

Reference 22

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raw_fallback, observed 2026-08-05T19:13:02.848983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:13:01.029933Z digest=sha256:672c4c9d0441221ab231c323f7c5fe818866564360a7c30b893d4ace3d1cc453

Observation 595350ec-749b-4b49-82ce-b36610744adc · outbound

This paper cites ALANINE: A Novel Decentralized Personalized Fed- erated Learning for Heterogeneous LEO Satellite Con- stellation.IEEE Transactions on Mobile Computing, 24(08):6945–6960, 2025.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations ALANINE: A Novel Decentralized Personalized Fed- erated Learning for Heterogeneous LEO Satellite Con- stellation.IEEE Transactions on Mobile Computing, 24(08):6945–6960, 2025

Reference 23

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raw_fallback, observed 2026-08-05T19:13:02.721089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:13:01.165892Z digest=sha256:ed8e35537942fe128799043498bf72f375573759234a329469b7e99a6bfec77e

Observation ebf48dac-eb8f-4e1b-86d8-4696554f3ea4 · outbound

This paper cites New: So2sat lcz42, 2019.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations New: So2sat lcz42, 2019

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-05T19:13:02.555709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:13:01.290994Z digest=sha256:98b28825c64556f576bdc019a985ae7a89af95b385c7ae1a3c43c10a24b0efe6

Observation 1cdd2939-f9e4-47db-840c-dcd7cf5050e9 · outbound

This paper cites Towards Satellite Non-IID Imagery: A Spectral Clustering-Assisted Federated Learning Approach.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations Towards Satellite Non-IID Imagery: A Spectral Clustering-Assisted Federated Learning Approach

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-05T19:13:01.671813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T19:13:01.421391Z digest=sha256:cd8950cf0ed38f515178b6b40e2efbfdfd07d8a3bda24e5d47f9e7100829d8e7

Pith citing papers

No inbound Pith citation observations are available.