Paper Citation Record · LEDGER

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data?

As of 10 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 5 inbound Pith citation observations for arXiv:2502.06555.

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

pith.paper-citation-record.v1
2502.06555 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:07:10.104376Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:09:04.098017Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T20:57:23.711824Z

Reference resolution

14 of 14 outbound references displayed

verified exact0
verified fuzzy0
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 085ca76e-22db-4542-9857-584d21c7ec64 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? Gemini: A Family of Highly Capable Multimodal Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.044837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a12fedf7-738b-4933-bcab-b1e138a89189 · outbound

This paper cites Harnessing large-language models to generate private synthetic text.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? Harnessing large-language models to generate private synthetic text

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.062722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation becaf1e2-f865-4600-9f7b-e76ae8b70f2c · outbound

This paper cites Differentially Private Synthetic Data via Foundation Model APIs 1: Images.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? Differentially Private Synthetic Data via Foundation Model APIs 1: Images

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.068657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2e226d3-2ad7-478d-abaf-669709ac5200 · outbound

This paper cites Winning the NIST Contest: A scalable and general approach to differentially private synthetic data.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? Winning the NIST Contest: A scalable and general approach to differentially private synthetic data

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.074443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4242d526-311d-48c6-bd67-93713067fecb · outbound

This paper cites Benchmarking Differentially Private Synthetic Data Generation Algorithms.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? Benchmarking Differentially Private Synthetic Data Generation Algorithms

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.089629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 019f74d0-e446-44c4-98ab-bce324e3a3f3 · outbound

This paper cites Differentially Private Tabular Data Synthesis using Large Language Models.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? Differentially Private Tabular Data Synthesis using Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.094727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95eb4bf7-f8b6-4949-b7a9-42747a1123bb · outbound

This paper cites Differentially Private Synthetic Data via Foundation Model APIs 2: Text.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? Differentially Private Synthetic Data via Foundation Model APIs 2: Text

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.099358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc53c47e-0516-46b0-87a9-760567ec4399 · outbound

This paper cites Tabular Data Synthesis with Differential Privacy: A Survey.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? Tabular Data Synthesis with Differential Privacy: A Survey

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.104376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cc3d626-bbd1-4ceb-9462-c728d1507a64 · outbound

This paper cites Kuntai Cai, Xiaoyu Lei, Jianxin Wei, and Xiaokui Xiao.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? Kuntai Cai, Xiaoyu Lei, Jianxin Wei, and Xiaokui Xiao

Reference 1996

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.039492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14500b73-b963-4a92-9b82-00bfaaeb0a3e · outbound

This paper cites PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs

Reference 2012

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.056944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data.

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 bb6c508b-63da-4386-a248-c709e04be67b · outbound

This paper cites Privately generating tabular data using language models.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? Privately generating tabular data using language models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.084334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6af842c8-0e5d-4621-af22-ca0d19f67a5a · outbound

This paper cites Differentially Private Diffusion Models Generate Useful Synthetic Images.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.051077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f47be36c-526f-40fb-97c1-b2fd7821e769 · outbound

This paper cites DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators

Reference 2024

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T15:07:10.382276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

Observation 879fd24d-a9dd-47cb-8c54-e9e715598013 · inbound

Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model cites this paper.

Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data?

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-08T19:09:04.098017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cb5d4fa-9a50-49d8-a927-03566a4ecf8e · inbound

Differentially Private Synthetic Data Release for Topics API Outputs cites this paper.

Differentially Private Synthetic Data Release for Topics API Outputs Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data?

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T21:38:48.176193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4caf204-c96a-4449-a1e5-eeade2c79602 · inbound

Concordia: Self-Improving Synthetic Tables for Federated LLMs cites this paper.

Concordia: Self-Improving Synthetic Tables for Federated LLMs Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data?

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:16:27.510957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1c63c6e7-d28d-4666-a4ed-abbc443d5f16 · inbound

Concordia: Self-Improving Synthetic Tables for Federated LLMs cites this paper.

Concordia: Self-Improving Synthetic Tables for Federated LLMs Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data?

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:23:47.975182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2df535aa-146b-444c-8040-dd3784f40235 · inbound

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

Differentially Private Synthetic Data via APIs 4: Tabular Data Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data?

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-02T20:57:23.713432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.