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Paper Citation Record · LEDGER

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

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 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 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:07:10.079578Z

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-24T08:13:32.915920Z digest=sha256:e6e1433fc54378bee6db299b07c71279b88e03c751dcdc251adda5b0ad0b406a

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.

source=pdf_text observed=2026-08-08T15:07:10.079578Z digest=sha256:171cc955ae28579836bd5af53f7b0547a8ca07c574d03246611f43fe11ced493

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-19T07:31:40.890140Z digest=sha256:9764667efe8e19039df9effbaad167b5da3aa600f3eae1ab113591eb19ed0623

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.

source=arxiv_source observed=2026-08-03T18:53:00.572529Z digest=sha256:309cf608b940d847549f4fb2a331973cecd97e830af185574a72a66929894055

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T09:47:19.376624Z digest=sha256:f75c1e6f95f52a991f3a5da4700c6874292b176fca70c0e6a807b292bae07996

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T09:30:05.317915Z digest=sha256:10f6856d330dc41fa1f6e2afabc71d885b346ab17e52a5f842936061b03152bc

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T15:21:15.470733Z digest=sha256:2e809d872270371e1faa9742dc7edfa62474a3527119f9fb87af1da35cd4c104

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-27T19:58:57.852382Z digest=sha256:0d1b2115c7af1eb55b2b38456b4c0c00330ad43b3e0f8a6b5b3afe7dfd2ec11a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-27T19:13:21.414587Z digest=sha256:f288b92c24ef233bda93606624ed34321ffcddaaf9f3357c706467f09760f8c0