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Paper Citation Record · LEDGER

Practical Blind Membership Inference Attack via Differential Comparisons

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2101.01341.

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

pith.paper-citation-record.v1
2101.01341 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:05:45.696069Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T09:23:16.085656Z

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 a2e5de4b-c103-4a22-80ae-199ad805632a · inbound

CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling cites this paper.

CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling Practical Blind Membership Inference Attack via Differential Comparisons

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-10T14:05:45.696069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:05:45.696069Z digest=sha256:f367208f461e6957f2a92f2c069805073af00ad36e35a640d3b08c04f2bd522d

Observation ae1bc712-aafa-476f-9cac-2ba6c2381dde · inbound

DocMIA: Document-Level Membership Inference Attacks against DocVQA Models cites this paper.

DocMIA: Document-Level Membership Inference Attacks against DocVQA Models Practical Blind Membership Inference Attack via Differential Comparisons

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-09T04:11:59.806746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:11:59.806746Z digest=sha256:768e29f65e9b887a72cf011137b3859b56969586ebf5e7784a6136031846642d

Observation f1d495e2-79e6-4452-944b-d2ad329660cd · inbound

LAPA-based Dynamic Privacy Optimization for Wireless Federated Learning in Heterogeneous Environments cites this paper.

LAPA-based Dynamic Privacy Optimization for Wireless Federated Learning in Heterogeneous Environments Practical Blind Membership Inference Attack via Differential Comparisons

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T14:13:34.758317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:13:34.758317Z digest=sha256:f85c5d501f66a49c18233a801136b588ff684170c630dd877d2f314ac71b8d81

Observation b383ab2c-9d3c-4d67-a2cf-17a66b6f1cb4 · inbound

Privacy-Utility Trade-off in Data Publication: A Bilevel Optimization Framework with Curvature-Guided Perturbation cites this paper.

Privacy-Utility Trade-off in Data Publication: A Bilevel Optimization Framework with Curvature-Guided Perturbation Practical Blind Membership Inference Attack via Differential Comparisons

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-05T11:59:40.392326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:59:40.392326Z digest=sha256:ce121e0faf60260d49a752786102b4006888126f3d38d7942709a99813a98094

Observation 9a21d494-55d7-43be-b1b0-054a1efa621f · inbound

A Full-Pipeline Framework for Evaluating Membership Inference Attacks in Machine Learning cites this paper.

A Full-Pipeline Framework for Evaluating Membership Inference Attacks in Machine Learning Practical Blind Membership Inference Attack via Differential Comparisons

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-06-29T09:23:16.087174Z

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=2026-06-29T09:20:39.053125Z digest=sha256:1995d568152a53ecc8ff09d79368da79e5d48d76e5f6e4a0fc8e85807f34a231