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Paper Citation Record · LEDGER

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

As of 7 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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:59:19.048450Z digest=sha256:ff6a6f6165ded47c7500e1b3c92e5ccc35a4df08a680e4a92c416637c0feefa9

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:59:19.178506Z digest=sha256:3000aa15679b8afaf6b505d6d80a026da86c7b5eebd587ec82df88c5c0432ded

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:59:19.343404Z digest=sha256:e54ea9d9f4d4e0dd788f76530d06e1a920596fb4fee023933aa8c25aaabbe2fb

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:59:19.429007Z digest=sha256:6e987603a2fd57feb791a698f4881e13c444c2433678b2ecb18e43c1a95057d0

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:59:19.581964Z digest=sha256:2eae2ad83b362fdf0388c2554661e099bb38904c7905c082119a4a22b44f83e6

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:59:19.717982Z digest=sha256:02e85949cdb6d9179fd50389c3fe1e79dcd463927130f57bca96dda0d8c137b5

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:59:19.857313Z digest=sha256:2525ee5906ea08a3a78bfb5f9b7d9595d4fbaaa52d23203ec4add52d14b20a45

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:59:19.958396Z digest=sha256:2267f169d548d2e8cb576f9713a308b793c494b31b0bba7cc3a5765b64c6ca4d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:59:20.061197Z digest=sha256:ad43aed3eafadb0c5805e5c25a47010ecb1d330db6f7d68858bf4831d52cdf30

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:59:20.150027Z digest=sha256:b0e764a778753dad1fb35eebd1fdd2a933d32f5c2ee98eaebb491a9122034fba

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:59:20.256989Z digest=sha256:297e2ca297be4201119e98089c517073142a4018c2f870364ecbad7704b32d3e

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T19:44:22.867192Z digest=sha256:a3b6372d5ceb1ae1ec3b7c9ff4ebe4dd06510f12040e3f0d857689c73af7b2d9