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Paper Citation Record · LEDGER

Federated Learning on Non-IID Data Silos: An Experimental Study

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2102.02079.

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

pith.paper-citation-record.v1
2102.02079 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T21:10:23.222453Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

82
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 8b8d13bf-f0f0-42e7-b914-af0e18f0f4cb · inbound

Exploit Gradient Skewness to Circumvent Byzantine Defenses for Federated Learning cites this paper.

Exploit Gradient Skewness to Circumvent Byzantine Defenses for Federated Learning Federated Learning on Non-IID Data Silos: An Experimental Study

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-08T21:10:23.222453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T21:10:23.222453Z digest=sha256:8e1fc7bc4678240726cccaca01823a611ea778d0278197d69b7ba761957d50c6

Observation 03ce907f-f1b6-477a-876c-da6ccb2f1f41 · inbound

DROP: Poison Dilution via Knowledge Distillation for Federated Learning cites this paper.

DROP: Poison Dilution via Knowledge Distillation for Federated Learning Federated Learning on Non-IID Data Silos: An Experimental Study

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-08T14:06:54.735418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T14:06:54.735418Z digest=sha256:4a91084aaba661c59aaa6f37c4e6621fe326cf8b7d683683a4c1db4419132916

Observation 8d84fb4a-c071-4788-ae19-6cf762a36e35 · inbound

Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity cites this paper.

Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity Federated Learning on Non-IID Data Silos: An Experimental Study

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T11:16:20.795118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:16:20.795118Z digest=sha256:56fde893b5a30ae677e9a7abbfcc0891b2fad336c05fd6352d805194859396cb

Observation 5ff7a6de-9535-4a02-9e9b-6f5938be6791 · inbound

Efficient Federated Learning with Timely Update Dissemination cites this paper.

Efficient Federated Learning with Timely Update Dissemination Federated Learning on Non-IID Data Silos: An Experimental Study

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-06T19:20:31.681560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:20:31.681560Z digest=sha256:6db6f1693a99d4d196c6ff378ddc2bca4805aa0571a81e4a2e8af9dbeab5acb3

Observation 675f2064-3b92-4c7f-8a08-8b34af5de9ae · inbound

Fairness in Federated Learning: Trends, Challenges, and Opportunities cites this paper.

Fairness in Federated Learning: Trends, Challenges, and Opportunities Federated Learning on Non-IID Data Silos: An Experimental Study

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-05T13:16:20.365497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:16:20.365497Z digest=sha256:e53f6a88b9e8b526f9ebe1b5b47f18eecb5991b5ae5b200997f9cfbc28421ff1

Observation 040637f5-b230-481c-915c-24448b283fdb · inbound

Automating aggregation strategy selection in federated learning cites this paper.

Automating aggregation strategy selection in federated learning Federated Learning on Non-IID Data Silos: An Experimental Study

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-10T17:35:40.313868Z

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=2026-05-10T17:32:03.728545Z digest=sha256:dc55ecd5888ecd2fc836f3f014ef16c3a6419163032491d06c102802514da778