Paper Citation Record · LEDGER

AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2201.12677.

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

pith.paper-citation-record.v1
2201.12677 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:57:47.637359Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T22:07:26.201898Z

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 7dd8d067-bad8-4fd9-b49f-84c26a246867 · inbound

ResidualPlanner+: a scalable matrix mechanism for marginals and beyond cites this paper.

ResidualPlanner+: a scalable matrix mechanism for marginals and beyond AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-24T08:14:10.120178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cd968ee9-a145-4fb1-8af7-be733751f478 · inbound

Are Data Experts Buying into Differentially Private Synthetic Data? Gathering Community Perspectives cites this paper.

Are Data Experts Buying into Differentially Private Synthetic Data? Gathering Community Perspectives AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-11T13:32:26.653161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c75609eb-7103-477f-b2d8-ff641e358dca · inbound

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? cites this paper.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.079578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5ec4f20-7e17-4bf1-ab01-ba44fabca92e · inbound

Aim High, Stay Private: Differentially Private Synthetic Data Enables Public Release of Behavioral Health Information with High Utility cites this paper.

Aim High, Stay Private: Differentially Private Synthetic Data Enables Public Release of Behavioral Health Information with High Utility AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-19T07:32:08.719864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 877017a2-b475-4338-b339-4b0c645303c0 · inbound

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

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T15:57:47.637359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1746abdf-9eaf-466d-a148-89000f8870f7 · inbound

How to DP-fy Your Data: A Practical Guide to Generating Synthetic Data With Differential Privacy cites this paper.

How to DP-fy Your Data: A Practical Guide to Generating Synthetic Data With Differential Privacy AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

Reference 159

Resolution: unresolved; no resolver link, observed 2026-08-03T18:53:00.572529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e79fa7a-b3cc-46d3-8f01-6d4ff49c48af · inbound

Decoupling Identity from Utility: Privacy-by-Design Frameworks for Financial Ecosystems cites this paper.

Decoupling Identity from Utility: Privacy-by-Design Frameworks for Financial Ecosystems AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T09:48:47.749986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e38de7e5-f752-4515-ade5-6f122bd33d06 · inbound

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance cites this paper.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:33:41.531103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 20b1cbe1-a835-419c-97e6-f806cc59102d · inbound

Private Adaptive Covariance Estimation via Gaussian Graphical Models cites this paper.

Private Adaptive Covariance Estimation via Gaussian Graphical Models AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-06-30T15:24:49.948671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7c868eee-63f4-41c7-832a-3254ec26ec12 · inbound

Differentially Private Synthetic Data via APIs 4: Tabular Data cites this paper.

Differentially Private Synthetic Data via APIs 4: Tabular Data AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T20:57:23.716287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 99709493-01bd-41e3-9360-7246c7a1d910 · inbound

SoK: Reconstruction Attacks on Synthetic Tabular Data (Insights from Winning the NIST CRC) cites this paper.

SoK: Reconstruction Attacks on Synthetic Tabular Data (Insights from Winning the NIST CRC) AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:07:26.203428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.