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Paper Citation Record · LEDGER

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study

As of 10 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2502.00182.

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

pith.paper-citation-record.v1
2502.00182 v3

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:57:19.479647Z

measured 24 of 24 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 2026-08-07T14:15:28.633807Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:15:30.051679Z

Reference resolution

23 of 23 outbound references displayed

  • verified exact0
  • verified fuzzy20
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7f2ed4d0-4507-4240-8345-74101a0e89ff · outbound

This paper cites In: ICLR (2021).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study In: ICLR (2021)

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.719454Z

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=2026-08-09T19:57:19.407302Z digest=sha256:1c0978d02a252c62a3b8bd1f24551a170cbd703f0eef9614269695545b546a92

Observation 6e0f43b9-eea6-44b9-8bbd-3426297f8bfa · outbound

This paper cites In: ICLR (2021).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study In: ICLR (2021)

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.710384Z

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=2026-08-09T19:57:19.412070Z digest=sha256:4885888d24513db68f413154dd146576abc0a1bb4db86f400a3ba3d5d8fb1532

Observation 84e68016-d6b5-4779-8cb4-1e327897278c · outbound

This paper cites NeurIPS (2006).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study NeurIPS (2006)

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.701320Z

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=2026-08-09T19:57:19.415479Z digest=sha256:53c5499c75c2bc7f5b10aa7b8bb806ed38a4d119deead44acefee0324c44d018

Observation 339eb239-479f-4e6e-9d64-3efc2e6582bb · outbound

This paper cites NeurIPS (2012).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study NeurIPS (2012)

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.692405Z

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=2026-08-09T19:57:19.418772Z digest=sha256:758da90828560eed910db35cae412305f6ce5697ea9f1252b93cc8d6edf07815

Observation 4c0661d3-c978-4a37-bf16-2791316a503a · outbound

This paper cites In: ICLR (2021).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study In: ICLR (2021)

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.683307Z

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=2026-08-09T19:57:19.422274Z digest=sha256:d40c00d90a24c1c8bd37c4809ffb15806b441d25238a46b530de3b6a1016936c

Observation 6a3c8e1c-4399-4177-9c03-39efe8332347 · outbound

This paper cites Foundations and trends in machine learning (2021).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study Foundations and trends in machine learning (2021)

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.673727Z

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 c5e90bcf-566b-40ec-9cfe-4d135ff79a4b · outbound

This paper cites In: ICML.

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study In: ICML

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.664224Z

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=2026-08-09T19:57:19.429375Z digest=sha256:9df042693560523bcf9b6b09bbc5de43db6bc26508d50c591d964a91bf2d00f9

Observation 5daae462-f4d5-4ff9-9dee-3ad6ba791958 · outbound

This paper cites In: ICLR (2017).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study In: ICLR (2017)

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.653879Z

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=2026-08-09T19:57:19.432492Z digest=sha256:3964bd40fea448b686df3f778aec39529bf1ec15a231c8b5bb78c2954ba69a83

Observation ea6294f7-c066-4071-89c0-8ea1028d8c31 · outbound

This paper cites In: CVPR (2024).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study In: CVPR (2024)

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.645074Z

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=2026-08-09T19:57:19.435735Z digest=sha256:cdd00ace7cf8423ae0ae7ac48193ef99c6fcfafb42a9bc66865a95266604e8f1

Observation 55114f0b-a41d-4128-a0e4-9cd397068788 · outbound

This paper cites NeurIPS (2022).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study NeurIPS (2022)

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.636059Z

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=2026-08-09T19:57:19.439071Z digest=sha256:580f097523b348338223c9f339b78f3810af7c017427a355db04916211e26f81

Observation dd24b965-d951-4e2a-ab96-a5048df69358 · outbound

This paper cites NeurIPS (2018).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study NeurIPS (2018)

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.626656Z

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=2026-08-09T19:57:19.442273Z digest=sha256:984d35739e586bbb789bdb5bc28a0373b75be46d05943796ea688a50009c9376

Observation 2e5ba8f0-25f6-43f6-9f86-9d52c1d4f501 · outbound

This paper cites In: CVPR (2021) Title Suppressed Due to Excessive Length 15.

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study In: CVPR (2021) Title Suppressed Due to Excessive Length 15

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.617250Z

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=2026-08-09T19:57:19.445356Z digest=sha256:efd402a700c550af9b2bb11e302dfa3669d5cd3328f0e752bb50ef074bfbdf78

Observation 0c542f90-45fe-43e7-9226-70de6f655356 · outbound

This paper cites MLSys (2020).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study MLSys (2020)

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.607283Z

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=2026-08-09T19:57:19.448526Z digest=sha256:5e82c1f8c79165e95f270c404c309a1d4bf74d5c5fdeb1f2cfe0b21c94b8edec

Observation 9f76a741-87ae-4917-bc94-25dd42196682 · outbound

This paper cites In: AISTATS.

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study In: AISTATS

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.597559Z

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=2026-08-09T19:57:19.451480Z digest=sha256:5ee8b2899a0943383648e24b26010a389e451ca497e4d89137378b473aa69791

Observation ab9fa6fc-597a-407d-8a5c-1f9415a476d3 · outbound

This paper cites In: ICML.

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study In: ICML

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.587555Z

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=2026-08-09T19:57:19.454500Z digest=sha256:427d936aa6c036e230a53a93a71a56ef181a4f64bd73d8ad783b4ac4375d468d

Observation 2eda2842-6d9c-4bf1-acd5-90c5e8bf7334 · outbound

This paper cites In: ICLR (2021).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study In: ICLR (2021)

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.577260Z

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=2026-08-09T19:57:19.457381Z digest=sha256:06e7c5d2891974e730613aaa2776f8ec191a794873cdf0da974e4163914ccbfe

Observation 7332f7ad-1de9-45a2-b9c1-663592e6307b · outbound

This paper cites An overview of gradient descent optimization algorithms.

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study An overview of gradient descent optimization algorithms

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-09T19:57:19.460289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:57:19.460289Z digest=sha256:2a4d289215f7cdacdb626cf54baefb7c5b9a1813390fb4dde6c13437f66342ba

Observation 6862694d-d459-4ab8-a928-a3f22f6811be · outbound

This paper cites Horovod: fast and easy distributed deep learning in TensorFlow.

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study Horovod: fast and easy distributed deep learning in TensorFlow

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-09T19:57:19.463843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:57:19.463843Z digest=sha256:0e07b258db5c8b9ac703cdd1004e1c7154fb2530e8c7ae87738d5b695f0ec851

Observation 1253b496-5bba-4c77-b1cc-13ab032c4431 · outbound

This paper cites In: ICLR (2019).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study In: ICLR (2019)

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.567411Z

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=2026-08-09T19:57:19.467158Z digest=sha256:612f543caa8926111baa1c624f60eb712431844c7a842d1bcf43aee4bc4f507d

Observation 7c9effa4-4058-446a-86d6-c44753fe6558 · outbound

This paper cites In: ICML.

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study In: ICML

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.557058Z

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=2026-08-09T19:57:19.469968Z digest=sha256:db88bcf7ab7052cfd00a0ac18528412bd195b83665d703d142589f5bca757afe

Observation 2af4501e-38dd-48cb-b8bd-7b74dc1628c1 · outbound

This paper cites In: ICML.

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study In: ICML

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.546959Z

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=2026-08-09T19:57:19.473159Z digest=sha256:e97cd47dc10f5f17696cd47be9bee45c127ffdb783c2647f7451b150cbd25570

Observation 02944cd8-1920-418c-a48d-e4d410fa481f · outbound

This paper cites Federated Learning with Non-IID Data.

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study Federated Learning with Non-IID Data

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-09T19:57:19.476164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:57:19.476164Z digest=sha256:585a9931c6df526c829e462e09ca62784bc1483b2a78a1bf490455ed935630b4

Observation 8797258c-f85a-4539-a020-c043918da888 · outbound

This paper cites NeurIPS (2010).

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study NeurIPS (2010)

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:57:19.536652Z

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=2026-08-09T19:57:19.479647Z digest=sha256:63f80f7464c6d9da5b442e869da615c5fba21c164ca946e39bfd8f5aea86fecb

Pith citing papers

Observation fcee1be4-4204-42fb-b7cb-65e397b49626 · inbound

Kuramoto-FedAvg: Using Synchronization Dynamics to Improve Federated Learning Optimization under Statistical Heterogeneity cites this paper.

Kuramoto-FedAvg: Using Synchronization Dynamics to Improve Federated Learning Optimization under Statistical Heterogeneity Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:15:30.104695Z

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=2026-08-07T14:15:28.633807Z digest=sha256:5ea6ba37cddd519320cfc37669e2eb668efb59464ae8a05b7118ce6f14e5875f