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Paper Citation Record · LEDGER

Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2009.03561.

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

pith.paper-citation-record.v1
2009.03561 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:40:12.049807Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T08:46:49.023153Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation ffa1de95-ad1a-440e-bc9d-7e123ffd217b · inbound

Metric Privacy in Federated Learning for Medical Imaging: Improving Convergence and Preventing Client Inference Attacks cites this paper.

Metric Privacy in Federated Learning for Medical Imaging: Improving Convergence and Preventing Client Inference Attacks Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-09T15:40:12.049807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:40:12.049807Z digest=sha256:bdc9b3e85accc714032a2a8b4c5e98116316a209f5eb350c75c9fbc7312161c4

Observation babcace2-9179-4050-abcf-ea25b8b6fd43 · inbound

Decoding FL Defenses: Systemization, Pitfalls, and Remedies cites this paper.

Decoding FL Defenses: Systemization, Pitfalls, and Remedies Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-09T14:12:23.309031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T14:12:23.309031Z digest=sha256:d5210fa2f7cec7c1a6fc1a1498d10beb3ad0ce424f85f1e2225552a9adb533ed

Observation 07e7bc06-2564-4ffa-be51-0066316c1f48 · inbound

FedGraM: Defending Against Untargeted Attacks in Federated Learning via Embedding Gram Matrix cites this paper.

FedGraM: Defending Against Untargeted Attacks in Federated Learning via Embedding Gram Matrix Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T15:43:21.295807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:43:21.295807Z digest=sha256:5692ccaec5dea0544178da2c18adcfb1a059d61777170040ea184abd04743e08

Observation c0b7364a-df6e-4da4-ba27-f9e313e64a7d · inbound

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix cites this paper.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T19:10:19.361450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:10:19.361450Z digest=sha256:5f3f7b573a29982103b64e96e02994555133f9a4fa8c96c9c4c8051aabb75cc6

Observation 321cd6ef-1b69-496f-9e9f-e98d01d5f984 · inbound

A Survey: Towards Privacy and Security in Mobile Large Language Models cites this paper.

A Survey: Towards Privacy and Security in Mobile Large Language Models Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-05T11:39:20.681479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:39:20.681479Z digest=sha256:75df73b4b536dd92cc2811669d11223b01596e356a1e7fb6e0c056add56a3799

Observation 833423c8-f5a8-45d4-84ab-2383a96ac75a · inbound

Revisiting Privacy Leakage in Machine Unlearning: Membership Inference Beyond the Forgotten Set cites this paper.

Revisiting Privacy Leakage in Machine Unlearning: Membership Inference Beyond the Forgotten Set Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:11:08.511358Z

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=2026-05-09T18:36:21.189195Z digest=sha256:3e03cca1beda37c4204d4fee75443a3b828d04445feb10846d74321d291bd099

Observation c2836293-a102-4c24-b237-2d7a622ad688 · inbound

Revisiting Privacy Leakage in Machine Unlearning: Membership Inference Beyond the Forgotten Set cites this paper.

Revisiting Privacy Leakage in Machine Unlearning: Membership Inference Beyond the Forgotten Set Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-07-01T07:35:28.941935Z

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=2026-07-01T07:30:02.278335Z digest=sha256:3d9cec1ba0eab8cc4d39d65732ec8a0a0e2ffc1eb5eca1afc86fdd5bc0a3bb22

Observation 9949a466-7248-4173-aba0-cb8548cfb81d · inbound

Adaptive Selection of LoRA Components in Privacy-Preserving Federated Learning cites this paper.

Adaptive Selection of LoRA Components in Privacy-Preserving Federated Learning Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:41:09.360866Z

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=2026-05-08T14:50:12.857642Z digest=sha256:b6ebc7713e4493487db25b501bba148908734abe47fd385860723b08bdfcd48e

Observation 5bb22763-5f54-4a62-98ec-06d90454221b · inbound

DIST-FL: Enhancing Security for TEE-based Aggregation in Federated Learning cites this paper.

DIST-FL: Enhancing Security for TEE-based Aggregation in Federated Learning Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-07-02T08:46:49.024588Z

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=2026-06-28T05:46:08.181285Z digest=sha256:172f2ba795df94827c523af1e21c6b0d80b3b340e54ad2725e7432250ee54a97