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Paper Citation Record · LEDGER

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy

As of 8 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 1 inbound Pith citation observation for arXiv:2507.12098.

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

pith.paper-citation-record.v1
2507.12098 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:59:20.256989Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:44:22.867192Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T19:44:23.126752Z

Reference resolution

11 of 11 outbound references displayed

  • verified exact0
  • verified fuzzy9
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e77357b5-8d85-4e85-bbd2-0228ba92da39 · outbound

This paper cites an unresolved cited work.

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:59:23.153624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:59:19.048450Z digest=sha256:b87e0f94bc5e51e826098dcc8dd4ef87fbe70386c6243520e01e2f32ed55d18f

Observation 3d230e05-3e00-4ccc-add5-41f4fff86bc9 · outbound

This paper cites ADPHE-FL: Federated learning method based on adaptive differential privacy and homomorphic encryption[J].

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy ADPHE-FL: Federated learning method based on adaptive differential privacy and homomorphic encryption[J]

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:59:22.983343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:59:19.178506Z digest=sha256:a8a7d0e069f8b5532912ab9b25bf5ec807ae18403139d1d1fcd529947b529c5b

Observation 5779acf1-70ce-457f-9ef8-0a0cb3e94705 · outbound

This paper cites A verifiable scheme for differential privacy based on zero-knowledge proofs[J].

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy A verifiable scheme for differential privacy based on zero-knowledge proofs[J]

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:59:22.813355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:59:19.343404Z digest=sha256:29aeb5063486ec712615042c774cbc150e151d37d09d5082f2ab4fdec8d448ec

Observation 40035dcf-fddb-4f44-8966-54094c799dcc · outbound

This paper cites Privacy-preserving heterogeneous multi-modal sensor data fusion via federated learning for smart healthcare[J].

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy Privacy-preserving heterogeneous multi-modal sensor data fusion via federated learning for smart healthcare[J]

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:59:22.466687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:59:19.429007Z digest=sha256:a86412ba68400d145e59f18de989005194c9b879bfb3958b1263703cfb71a9a6

Observation bd3fa1a2-4646-4538-bdc0-18d34753a856 · outbound

This paper cites Group verifiable secure aggregate federated learning based on secret sharing[J].

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy Group verifiable secure aggregate federated learning based on secret sharing[J]

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:59:22.301696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:59:19.581964Z digest=sha256:7c101caefe4f2b0a5e6174a2cdf8772260173092abc02ed0fb75f8637be29149

Observation 3ca5cbf0-6bec-43e3-9c9b-25b5e100c37a · outbound

This paper cites Fed-MWFP: Lightweight federated learning with interpretable multiple wavelet fusion network for fault diagnosis under variable operating conditions[J].

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy Fed-MWFP: Lightweight federated learning with interpretable multiple wavelet fusion network for fault diagnosis under variable operating conditions[J]

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:59:21.977581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:59:19.717982Z digest=sha256:69a959fc9a22d3988278fbe2a9d81a10eb095c7acee8566ae33c2e46fba24e1a

Observation 9a2988ae-71a1-4867-9974-edf78c5de41a · outbound

This paper cites Leveraging Transfer Learning Domain Adaptation Model with Federated Learning to Revolutionize Healthcare[J].

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy Leveraging Transfer Learning Domain Adaptation Model with Federated Learning to Revolutionize Healthcare[J]

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:59:21.751116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:59:19.857313Z digest=sha256:dc4c8fe7a1dd051d22ea9882a05e606ab11cbdd8e3b5eda1efdcee37a7d22460

Observation 0490d6d4-e962-400b-b2f1-bfee11b3d674 · outbound

This paper cites Consumers' information control and privacy concerns in personalized social media advertising[J].

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy Consumers' information control and privacy concerns in personalized social media advertising[J]

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:59:21.527643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:59:19.958396Z digest=sha256:14c55cb8e061613dea89c37c0f5cc8db894048f4639b14a91dc8ef94a6feb7f9

Observation e7a02be5-79cd-49f5-aaa6-a59712d1b87b · outbound

This paper cites Research on Personalized Recommendation of Mobile Advertising Based on Content Filtering Interest Model[J].

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy Research on Personalized Recommendation of Mobile Advertising Based on Content Filtering Interest Model[J]

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:59:21.197981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:59:20.061197Z digest=sha256:ebd2bc244b2319b5e9344367659175f8d5fc42bca2297bb6413fe69d91af3401

Observation 9b2f1433-3abd-4817-bfd4-86349d7e3289 · outbound

This paper cites Personalized charity advertising.

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy Personalized charity advertising

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:59:20.883100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:59:20.150027Z digest=sha256:1859ac9254ce038c208887a6869284473415b76020fde699651cb499f9f5270f

Observation ecc1fcbf-2885-4ec6-a2a2-69435aa4fe49 · outbound

This paper cites an unresolved cited work.

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:59:20.595864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:59:20.256989Z digest=sha256:3ef3bc56779d9a6a105af6c68798fcad9078be739f0f2e47d5a4305f839808bf

Pith citing papers

Observation 6a017ee0-214c-42c4-973c-559ad2d5d11c · inbound

CAMF: Collaborative Adversarial Multi-agent Framework for Machine Generated Text Detection cites this paper.

CAMF: Collaborative Adversarial Multi-agent Framework for Machine Generated Text Detection A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-05T19:44:23.130353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T19:44:22.867192Z digest=sha256:08e78bcd65fd69f7096b75e0a849b4cccc886a9a5f4c1861c0c795a3d6966de6