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Paper Citation Record · LEDGER

Formalizing and Estimating Distribution Inference Risks

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2109.06024.

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

pith.paper-citation-record.v1
2109.06024 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:37:36.393954Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:37:30.284495Z

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 f74b0d37-7dcf-409e-a7ca-d24675f021f3 · inbound

Statistic Maximal Leakage cites this paper.

Statistic Maximal Leakage Formalizing and Estimating Distribution Inference Risks

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-12T11:17:14.561784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:17:14.561784Z digest=sha256:6d2b7e5d78863afc0a37b410aff5b979427cebfa55fcb7f755c9a4e0f3fd2d63

Observation 3bf08ac5-ee0c-47ea-af86-ba018a230d97 · inbound

On Linear Representations and Pretraining Data Frequency in Language Models cites this paper.

On Linear Representations and Pretraining Data Frequency in Language Models Formalizing and Estimating Distribution Inference Risks

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-16T12:37:36.393954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:37:36.393954Z digest=sha256:638143a7de4c4d4beca276b72732f0ba9c48ae7ecf8b13cb4055d9a7c2a94b78

Observation b8618376-17eb-4222-b60c-303d2c84d7a2 · inbound

SoK: Data Reconstruction Attacks Against Machine Learning Models: Definition, Metrics, and Benchmark cites this paper.

SoK: Data Reconstruction Attacks Against Machine Learning Models: Definition, Metrics, and Benchmark Formalizing and Estimating Distribution Inference Risks

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-07T05:29:46.725458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:29:46.725458Z digest=sha256:f9305cda85dedae78ab367a9e32d871b9cabe92a2ef13397d63341778bea9cad

Observation 5a2228e5-a22c-4234-8d11-810158442188 · inbound

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation cites this paper.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Formalizing and Estimating Distribution Inference Risks

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-15T15:57:47.670973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:57:47.670973Z digest=sha256:bc29b965e5d235e2ef55bd3ab72c81ebabae3a4a7782bf61c49447311c8bb18c

Observation fb7d7674-b13d-4354-8549-b5c02217a449 · inbound

Fair Finetuning Mitigates Distribution Inference Attacks cites this paper.

Fair Finetuning Mitigates Distribution Inference Attacks Formalizing and Estimating Distribution Inference Risks

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-07-01T21:56:15.475291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-28T16:05:53.398690Z digest=sha256:a5f59ed489f08decd861fcd46d68f22450f9f208e58fafd7e59428be2dacc743

Observation 1f7ec0d0-1bc1-4b5c-8033-dd7cc8759521 · inbound

Alignment Defends LLMs from Property Inference Attacks cites this paper.

Alignment Defends LLMs from Property Inference Attacks Formalizing and Estimating Distribution Inference Risks

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:37:30.285981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-27T17:05:19.853450Z digest=sha256:82430af3d826f86e9df964bd10f0f60746105d6006b90daa06fcfc787fb69435