Paper Citation Record · LEDGER

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance

As of 16 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2604.15660.

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

pith.paper-citation-record.v1
2604.15660 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T09:30:05.317915Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

25 of 25 outbound references displayed

verified exact2
verified fuzzy22
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5bcf3bac-1623-49ec-be03-760da787849f · outbound

This paper cites Data synthesis via differentially private markov random fields.Proceedings of the VLDB Endow- ment, 14(11):2190–2202.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance Data synthesis via differentially private markov random fields.Proceedings of the VLDB Endow- ment, 14(11):2190–2202

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.431640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c0f58c40-b498-4433-8642-e354915876cf · outbound

This paper cites PrivPetal: Relational data synthesis via permutation rela- tions.Proceedings of the ACM on Management of Data, 3(3):1–26.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance PrivPetal: Relational data synthesis via permutation rela- tions.Proceedings of the ACM on Management of Data, 3(3):1–26

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.434225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a5a68581-0c3b-43fa-a626-cd8e51db052d · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance Imagenet: A large-scale hierarchical image database

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.422454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 03ffef87-7aa9-4ad6-bd28-7e0c7f1209ca · outbound

This paper cites The algorithmic foundations of differential privacy.F ounda- tions and trends® in theoretical computer science, 9(3– 4):211–407.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance The algorithmic foundations of differential privacy.F ounda- tions and trends® in theoretical computer science, 9(3– 4):211–407

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.415876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4f41ee11-8963-439d-8298-599c11ab8891 · outbound

This paper cites Exploring distribution learning of synthetic data genera- tors for manifolds.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance Exploring distribution learning of synthetic data genera- tors for manifolds

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.417720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 81778a60-09dd-474d-a7c7-091dd481b6eb · outbound

This paper cites A survey of generative adversarial networks for synthesizing structured electronic health records.ACM Computing Surveys, 56(6):1–34.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance A survey of generative adversarial networks for synthesizing structured electronic health records.ACM Computing Surveys, 56(6):1–34

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.440256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3d5b221a-a23a-461b-9ca5-0998be21fbef · outbound

This paper cites A simple and practical algorithm for differen- tially private data release.Advances in neural information processing systems, 25.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance A simple and practical algorithm for differen- tially private data release.Advances in neural information processing systems, 25

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.431848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c52937d0-bb97-4ed4-af87-3d7754b604db · outbound

This paper cites Deep residual learning for image recog- nition.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance Deep residual learning for image recog- nition

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.420126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 229448e6-7d7a-4ea3-9fc3-fd5c06166e36 · outbound

This paper cites WDP-GAN: Weighted graph gener- ation with gan under differential privacy.IEEE Transac- tions on Network and Service Management, 20(4):5155– 5165.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance WDP-GAN: Weighted graph gener- ation with gan under differential privacy.IEEE Transac- tions on Network and Service Management, 20(4):5155– 5165

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.437692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e2a37257-c213-4748-8213-13826551821b · outbound

This paper cites ABSyn: An accurate differentially private data syn- thesis scheme with adaptive selection and batch processes.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance ABSyn: An accurate differentially private data syn- thesis scheme with adaptive selection and batch processes

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.442902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2ad5db37-64bd-4252-b336-44da6bcfaae3 · outbound

This paper cites Scaling up the accuracy of naive-bayes classifiers: A decision-tree hybrid.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance Scaling up the accuracy of naive-bayes classifiers: A decision-tree hybrid

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.437488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 051d609f-7165-490f-940e-736058a15e0d · outbound

This paper cites an unresolved cited work.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-05-20T17:13:36.426495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2da3f5f6-7c04-4fcb-87b7-38df3f99d1c9 · outbound

This paper cites Sphinx- x: scaling data and parameters for a family of multi-modal large language models.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance Sphinx- x: scaling data and parameters for a family of multi-modal large language models

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.433992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation acf60490-d2d4-49e2-ae7b-6dc6bb1c6e47 · outbound

This paper cites RDP-GAN: A r ´enyi-differential privacy based generative adversarial network.IEEE Transactions on Dependable and Secure Computing, 20(6):4838–4852.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance RDP-GAN: A r ´enyi-differential privacy based generative adversarial network.IEEE Transactions on Dependable and Secure Computing, 20(6):4838–4852

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.445721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 350ff6f8-9080-4017-9fe6-e4df51cccc98 · outbound

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

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance Winning the NIST Contest: A scalable and general approach to differentially private synthetic data

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:33:41.527666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

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

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 2026-08-16T06:30:59.297886+00:00.

Observation 3aa76d83-a9b2-4ca8-a0ab-b1b82e215364 · outbound

This paper cites Smoking signal of body classification dataset.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance Smoking signal of body classification dataset

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.457196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0ba806ec-a457-41ec-b730-7d097c51199c · outbound

This paper cites [Ruggleset al., 2015 ] Steven Ruggles, Katie Genadek, Ronald Goeken, Josiah Grover, and Matthew Sobek.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance [Ruggleset al., 2015 ] Steven Ruggles, Katie Genadek, Ronald Goeken, Josiah Grover, and Matthew Sobek

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.459193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bb9191c0-5eb2-4481-82ce-24d72390969f · outbound

This paper cites Liver disease patient dataset.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance Liver disease patient dataset

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.459009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9aaaddb0-0997-448a-b13e-6bcc15b2d0cb · outbound

This paper cites [Srivastava and Alzantot, 2019] Mani Srivastava and Moustafa Alzantot.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance [Srivastava and Alzantot, 2019] Mani Srivastava and Moustafa Alzantot

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.447945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f57f1781-21f9-480c-8748-931a2b480b5e · outbound

This paper cites [Wanget al., 2025 ] Suqing Wang, Zuchao Li, Shi Luohe, Bo Du, Hai Zhao, Yun Li, and Qianren Wang.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance [Wanget al., 2025 ] Suqing Wang, Zuchao Li, Shi Luohe, Bo Du, Hai Zhao, Yun Li, and Qianren Wang

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.460934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bdb2707e-cbc6-43ed-a674-2891ac8096f2 · outbound

This paper cites Redpajama: an open dataset for train- ing large language models.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance Redpajama: an open dataset for train- ing large language models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.463280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 091784c4-5aba-47a8-b108-e2d834f98a4e · outbound

This paper cites [Yeet al., 2024 ] Rui Ye, Wenhao Wang, Jingyi Chai, Dihan Li, Zexi Li, Yinda Xu, Yaxin Du, Yanfeng Wang, and Si- heng Chen.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance [Yeet al., 2024 ] Rui Ye, Wenhao Wang, Jingyi Chai, Dihan Li, Zexi Li, Yinda Xu, Yaxin Du, Yanfeng Wang, and Si- heng Chen

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.465067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 15c6bbdd-dcc2-4631-88b8-a98e3a0178b5 · outbound

This paper cites Data-centric artificial intelligence: A survey.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance Data-centric artificial intelligence: A survey

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.454772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9583515f-eaf4-4d2b-9e40-dd3d0cc6bb03 · outbound

This paper cites PrivSyn: Differentially private data synthesis.

DPDSyn: Improving Differentially Private Dataset Synthesis for Model Training by Downstream Task Guidance PrivSyn: Differentially private data synthesis

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T17:13:36.457040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

No inbound Pith citation observations are available.