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Paper Citation Record · LEDGER

State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2404.16847.

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

pith.paper-citation-record.v1
2404.16847 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:02:34.462653Z

measured 1 of 1 external citation measurements

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

Source: pith, 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

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4aa22c69-6b9a-47bd-b8f4-757517ec13ef · inbound

Privacy-Preserving Large Language Models: Mechanisms, Applications, and Future Directions cites this paper.

Privacy-Preserving Large Language Models: Mechanisms, Applications, and Future Directions State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-11T20:02:34.462653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:02:34.462653Z digest=sha256:b91779f02aae6ea533b69e42de80d438c4cced03382732082d0ee69cf4b37903

Observation 9b2a51e6-d446-4041-a517-5ad33c005889 · inbound

Accelerating Sparse Graph Neural Networks with Tensor Core Optimization cites this paper.

Accelerating Sparse Graph Neural Networks with Tensor Core Optimization State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-11T15:03:54.583986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:03:54.583986Z digest=sha256:9938ecaffe73bcdcdd8fe7b5f64c4d5d01895402aed1292e5a1a97e0ab74dd14

Observation c3e54711-45c9-44cc-9f76-f26fdec4f58b · inbound

Blockchain-Based Secure Vehicle Auction System with Smart Contracts cites this paper.

Blockchain-Based Secure Vehicle Auction System with Smart Contracts State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T21:26:47.889887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:26:47.889887Z digest=sha256:0a80c7dd6cc7f75fb60b63fd623529da7da88c8409703b0a6985916c45fc83da

Observation 36e5c429-cb58-4bbb-9861-c8d7818e404f · inbound

StarCast: A Secure and Spectrum-Efficient Group Communication Scheme for LEO Satellite Networks cites this paper.

StarCast: A Secure and Spectrum-Efficient Group Communication Scheme for LEO Satellite Networks State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-08T11:31:33.556007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:31:33.556007Z digest=sha256:f70206bdbea46421fa24b1b5d22c9220f14dbb78b47b0877ca23daccb9458c54

Observation f464d4ed-f67a-4a4e-9f9a-e9c1d4d01f90 · inbound

Enabling Trustworthy Federated Learning via Remote Attestation for Mitigating Byzantine Threats cites this paper.

Enabling Trustworthy Federated Learning via Remote Attestation for Mitigating Byzantine Threats State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T13:28:45.802331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:28:45.802331Z digest=sha256:af2dc67bf44a879b61808518ef30001f91b57acfde8a1122d614464d5cddbf26

Observation 181c5f80-885c-4cee-91fd-75ab35fb4a2d · inbound

Closing the Visibility Gap: A Monitoring Framework for Verifiable Open RAN Operations cites this paper.

Closing the Visibility Gap: A Monitoring Framework for Verifiable Open RAN Operations State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-05T11:18:11.794876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:18:11.794876Z digest=sha256:a35cf5a1e75d79275d2f2adda82f8c2e66a92c8ede1bfc9240e8bda389e53011

Observation 22d7cbec-6b1f-495d-bcfa-741b35df8ae0 · inbound

Metaverse in Smart Cities: Transforming Urban Life and Governance cites this paper.

Metaverse in Smart Cities: Transforming Urban Life and Governance State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey

Reference 131

Resolution
verified exact
arxiv_id, observed 2026-07-05T10:00:53.409233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-05T09:51:21.357161Z digest=sha256:26462ddbaedbdd29eb80efb871da6c14288a71340f45c3d1c80f84129edc789d

Observation dd35e5f6-6bd8-4d18-acd3-ff5eff2fc135 · inbound

POPS: Recovering Unlearned Multi-Modality Knowledge in MLLMs with Prompt-Optimized Parameter Shaking cites this paper.

POPS: Recovering Unlearned Multi-Modality Knowledge in MLLMs with Prompt-Optimized Parameter Shaking State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-07-11T00:27:50.642217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-11T00:23:30.377235Z digest=sha256:eada03bf42931697a64be94e7d00ac8eca8174a2857e1b5218d98db6ed9ee00b