Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T15:07:10.079578Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T22:07:26.201898Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 7dd8d067-bad8-4fd9-b49f-84c26a246867 · inbound
ResidualPlanner+: a scalable matrix mechanism for marginals and beyond AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data
Reference 40
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.
Observation c75609eb-7103-477f-b2d8-ff641e358dca · inbound
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
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 AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data
Reference 7
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.
Observation 1746abdf-9eaf-466d-a148-89000f8870f7 · inbound
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
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 AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data
Reference 10
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.
Observation e38de7e5-f752-4515-ade5-6f122bd33d06 · inbound
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
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.
Observation 20b1cbe1-a835-419c-97e6-f806cc59102d · inbound
Private Adaptive Covariance Estimation via Gaussian Graphical Models AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data
Reference 22
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.
Observation 7c868eee-63f4-41c7-832a-3254ec26ec12 · inbound
Differentially Private Synthetic Data via APIs 4: Tabular Data AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data
Reference 10
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.
Observation 99709493-01bd-41e3-9360-7246c7a1d910 · inbound
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
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.