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Paper Citation Record · LEDGER

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning

As of 9 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2507.11430.

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

pith.paper-citation-record.v1
2507.11430 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:13:28.019764Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

27 of 27 outbound references displayed

  • verified exact1
  • verified fuzzy17
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a872589c-204d-4ca1-a169-f5560f0593c0 · outbound

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

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Communication- efficient learning of deep networks from decentralized data

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:32.431429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:25.722632Z digest=sha256:d8511c9f9cdda136003bb3b3f997a72d55f987c8340310c720ac0da4b3838393

Observation 0eb49e03-a543-401f-a530-46985195e2cf · outbound

This paper cites Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T17:13:25.795161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:13:25.795161Z digest=sha256:86be74e451cc9b1f7bc7db1e07bb3d523e71b4d5c445f21b97d33d15f9040af0

Observation ca62247b-c42f-4f64-80c4-d3072ecaca92 · outbound

This paper cites Federated optimization in heterogeneous networks.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Federated optimization in heterogeneous networks

Reference 3

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no resolver link, observed 2026-08-06T17:13:25.874506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:13:25.874506Z digest=sha256:291549286027c01267b5d8edd7b4343d889a40e8ebb1462b626cca10b5e30b87

Observation 7c0a6d4b-0712-49d8-b161-72cae6065e87 · outbound

This paper cites Model-contrastive federated learning.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Model-contrastive federated learning

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:32.148526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:26.000816Z digest=sha256:2c17546b40c5d190e6aa7cde1c87e80e3c042232a98ff56a0283d4eb2f481d31

Observation 42c5991c-31fa-4954-a0cb-a20425e588d0 · outbound

This paper cites Scaffold: Stochastic controlled averaging for federated learning.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Scaffold: Stochastic controlled averaging for federated learning

Reference 5

Resolution
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no resolver link, observed 2026-08-06T17:13:26.087143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:13:26.087143Z digest=sha256:fb500b8466100854b5bfadcfed456733a29a8ccce413f636937e8273b56b3ec9

Observation ba52c078-6e7e-42fe-9e3a-9d7a70eb5501 · outbound

This paper cites Adaptive Federated Optimization.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Adaptive Federated Optimization

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T17:13:26.170126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:13:26.170126Z digest=sha256:8964130a9b8a02d2b3caa9c1353f5632321e8e339969700d18f3a9b4753a5c3a

Observation 4ff63e87-c214-4528-9dca-e65f26c03c34 · outbound

This paper cites Differentially Private Federated Learning: A Client Level Perspective.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 7

Resolution
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no resolver link, observed 2026-08-06T17:13:26.235364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:13:26.235364Z digest=sha256:ac03667b97e9a0c782dabc9749e59920605d6ef00450779dae45d5afaa5db040

Observation 417a3987-f7f8-4a1c-81c2-3b8c092c4857 · outbound

This paper cites Pcfed: Privacy-enhanced and communication-efficient federated learning for industrial iots.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Pcfed: Privacy-enhanced and communication-efficient federated learning for industrial iots

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:31.959574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:26.326283Z digest=sha256:7ec3d9c75ffa57a11b459fb023e6b1deec4af5be419d9998707ec8929f9e5811

Observation 1eda3d26-26f2-4b65-af4e-80e572e031db · outbound

This paper cites Federated Learning with Matched Averaging.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Federated Learning with Matched Averaging

Reference 9

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unresolved
no resolver link, observed 2026-08-06T17:13:26.380042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:13:26.380042Z digest=sha256:8cffdb47e1b798417adafce0d800cd773150739b480eba8941e2d5e11eb627c0

Observation c015ea4a-1dd1-4af8-9b12-02d40803181b · outbound

This paper cites Federated Learning with Personalization Layers.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Federated Learning with Personalization Layers

Reference 10

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unresolved
no resolver link, observed 2026-08-06T17:13:26.442027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:13:26.442027Z digest=sha256:d4f789b45409e5d5423ad86c78dcd3a275e48c76402d01dc01de3f1b533f2877

Observation 41ccbb83-483d-4f4b-9f76-537e8c1ed9a6 · outbound

This paper cites Grace: A generalized and personalized federated learning method for medical imaging.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Grace: A generalized and personalized federated learning method for medical imaging

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:31.693855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:26.517654Z digest=sha256:272ebfb5cf2d16c8fd4b526dd5710fd3776bff50ec52020789fc0cccb2b940a2

Observation fbd633f4-71a8-4935-a971-e15f7feb18d0 · outbound

This paper cites A greedy agglomerative framework for clustered federated learning.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning A greedy agglomerative framework for clustered federated learning

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:31.470619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:26.596390Z digest=sha256:5a746ac9fbdd266cb4509aa55512a2b3d2d6e41100af96661a20504aad117bbc

Observation 3189cdd1-33ca-45c6-a33e-dfb4818a3b7e · outbound

This paper cites Fedrlchain: Secure federated deep reinforcement learning with blockchain.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Fedrlchain: Secure federated deep reinforcement learning with blockchain

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:31.238615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:26.660706Z digest=sha256:255a9634861ba768f779efc01a9c81dda53e1858f44b79ceb398aca91258fc94

Observation 8a8ddd31-f5ee-479c-93ca-5330adc376c5 · outbound

This paper cites Blockchain-based federated learning with secure aggregation in trusted execution envi- ronment for internet-of-things.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Blockchain-based federated learning with secure aggregation in trusted execution envi- ronment for internet-of-things

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:31.040564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:26.719867Z digest=sha256:60bd0d0569c3a15986981741a45ce28aaeb89bf34132d366c016e93ee619341c

Observation 384e1c6b-207c-43e0-9840-5a332fa647f9 · outbound

This paper cites Federated active semi-supervised learning with communication efficiency.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Federated active semi-supervised learning with communication efficiency

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:30.736792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:26.789329Z digest=sha256:42ad053a67545b75d56d443bce6b6757d3b30b3b320a2bbdb1a3dc88dfd11b6e

Observation 2ff29200-6948-48eb-a1dc-272b0ecb45e9 · outbound

This paper cites Fedstream: Prototype-based federated learning on distributed concept-drifting data streams.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Fedstream: Prototype-based federated learning on distributed concept-drifting data streams

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:30.546514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:26.881391Z digest=sha256:2cbc1cf66482abdca39ef7462121565f32b46100f034cd3b1022ecf228b9419d

Observation 2ec4dda8-717c-4d8d-b2de-9cc4a8080c2c · outbound

This paper cites https://www.tensorflow.org/federated.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning https://www.tensorflow.org/federated

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:30.317721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:26.964978Z digest=sha256:7ca4fb11ca8f933eebba7ba8586d5cb106ee681ed9db56e66ed9ff68bc10e0ae

Observation b60a7da2-6d0e-4368-bdb2-9cd2cc766503 · outbound

This paper cites Pysyft: A library for easy federated learning.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Pysyft: A library for easy federated learning

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:30.092260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:27.062995Z digest=sha256:2810c1a627a648643d6abc193cefb984b9a68093579bb7767081afed08df1892

Observation df7ebf78-538f-4606-ad5a-2a73c3e4676a · outbound

This paper cites Fate: An industrial grade platform for collaborative learning with data protection.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Fate: An industrial grade platform for collaborative learning with data protection

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-06T17:13:29.887006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:27.171264Z digest=sha256:af772fcea2c2f558ceda9d31a424bc2ed62c657a4daa2f02b09e4b7709ac7cbf

Observation 2cab63bf-7aee-4d07-95b7-51ca1784e2e6 · outbound

This paper cites Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:13:28.326096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:27.267423Z digest=sha256:3e9a678d7829cb71fb224cb7fc08b25f2f08094e6c865cc215f37e80b611169e

Observation b132323d-de81-4b86-846c-3da64a2f37da · outbound

This paper cites Flower: A Friendly Federated Learning Research Framework.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Flower: A Friendly Federated Learning Research Framework

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T17:13:27.340926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:13:27.340926Z digest=sha256:0aefaaa2a45b80fe809ae5992e809bc97ab6052dc33ced51e82ab8495bb23922

Observation 8feffcfd-3d76-4864-9a28-e23090d467c0 · outbound

This paper cites Fedlab: A flexible federated learning frame- work.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Fedlab: A flexible federated learning frame- work

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:29.575493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:27.475295Z digest=sha256:f58a2651098ebbf680285a7b425a9ecdb2c54ad1fee40a7131bb0ee9a73ddfe9

Observation 7108ee1c-518a-499f-b670-e0e6807818fe · outbound

This paper cites FedML: A Research Library and Benchmark for Federated Machine Learning.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning FedML: A Research Library and Benchmark for Federated Machine Learning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T17:13:27.595839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:13:27.595839Z digest=sha256:af04a97d7a73e3a59aefee5a3d6d1356d7897f0206207cdeb34b094d314f3e8b

Observation 2e631b71-08b0-434f-845c-52cfbc4d2c9d · outbound

This paper cites Fedstellar: A platform for decentralized federated learning.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Fedstellar: A platform for decentralized federated learning

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:29.345218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:27.713293Z digest=sha256:d646af62b8eeef49b4e167d74d4728a04d9a9aecee4d920c4d6b99f22a25f5b1

Observation 71c56878-6660-4669-b105-232e3322da39 · outbound

This paper cites Deepchain: Auditable and privacy- preserving deep learning with blockchain-based incentive.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Deepchain: Auditable and privacy- preserving deep learning with blockchain-based incentive

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:29.142912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:27.799360Z digest=sha256:3154b98710755451d824ab52b9731bc4a9aeb3b7c173ccbc0a452d5c6241040d

Observation 639b540b-80ee-4763-842e-e189c45e28d5 · outbound

This paper cites Federated learning with hierarchical clustering of local up- dates to improve training on non-iid data.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Federated learning with hierarchical clustering of local up- dates to improve training on non-iid data

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:28.914396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:27.897065Z digest=sha256:56043acfcd8eab4f9a487333c34eca863ae3ded053428fb61eaef46e33100487

Observation 70351060-65a8-46ba-aded-2e55ef55ce42 · outbound

This paper cites 1,500 scientists lift the lid on reproducibility.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning 1,500 scientists lift the lid on reproducibility

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:13:28.668843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:13:28.019764Z digest=sha256:eb6299612402d0a71b702f90b572ddbdc4452137f740497dbd642d59fb7f7fe7

Pith citing papers

No inbound Pith citation observations are available.