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Paper Citation Record · LEDGER

Differentially Private Diffusion Models Generate Useful Synthetic Images

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2302.13861.

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

pith.paper-citation-record.v1
2302.13861 v1

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 2026-08-06T06:34:29.942622+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:12:33.396844Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-11T01:47:47.905189Z

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 d2823d9c-dc27-4380-99e2-ae38a5652214 · inbound

CollaFuse: Collaborative Diffusion Models cites this paper.

CollaFuse: Collaborative Diffusion Models Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-23T23:35:52.201089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-23T23:35:00.048503Z digest=sha256:c1035bc8ca4f1af90d2540551c7e5bc3bcabd3c8990b1fcedf08448b22f0c9d6

Observation 103d1ab8-dc8e-42a4-b23b-15d773f70d6e · inbound

Privacy Leakage via Output Label Space and Differentially Private Continual Learning cites this paper.

Privacy Leakage via Output Label Space and Differentially Private Continual Learning Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 47

Resolution
metadata mismatch
arxiv_id, observed 2026-05-23T17:23:15.470770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-23T17:18:22.300467Z digest=sha256:31ca7eddeb7bfb2b10531504501f889f1086465f7517383000f919bebe103bb1

Observation 8475ac6b-768b-4585-8965-4a3c27e1a75f · inbound

Implementing Adaptations for Vision AutoRegressive Model cites this paper.

Implementing Adaptations for Vision AutoRegressive Model Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T17:12:33.396844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:12:33.396844Z digest=sha256:41fc27c5114b0fe159113996e05d01a0e0108bfb31cd3c341352f9125da3da45

Observation a80cdf79-fa5a-4a70-874f-75b6fd987053 · inbound

Improving Noise Efficiency in Privacy-preserving Dataset Distillation cites this paper.

Improving Noise Efficiency in Privacy-preserving Dataset Distillation Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T05:32:44.944068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:32:44.944068Z digest=sha256:e174c7aab6bab1c4e2d2d1a7e84ca3e0b99d65854e58eed5854cccbaff1398d9

Observation ccb58872-9a6e-4e63-a81f-b64db7d6de84 · inbound

DP-DocLDM: Differentially Private Document Image Generation using Latent Diffusion Models cites this paper.

DP-DocLDM: Differentially Private Document Image Generation using Latent Diffusion Models Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T00:51:45.214645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:51:45.214645Z digest=sha256:f065e3ca05a68ad18b9d6be5b3f10471146de8be356e238217e507d6283fa0d4

Observation b3581325-4cc7-4c23-b8e6-786f465d26ad · inbound

DP-SAPF: Saliency-Aware Parameter Fine-tuning of Public Models for Differentially Private Image Synthesis cites this paper.

DP-SAPF: Saliency-Aware Parameter Fine-tuning of Public Models for Differentially Private Image Synthesis Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T14:33:30.899539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-29T06:39:55.821587Z digest=sha256:616695714f92ce811ff49eb542e9e1fab359e4ac5e51d3bfa5e91c6fdb95317b

Observation 55e9ead4-2186-4a12-8a0d-f50bf481c090 · inbound

PeerCheck: Enhancing LLM-Generated Academic Reviews Towards Human-Level Quality cites this paper.

PeerCheck: Enhancing LLM-Generated Academic Reviews Towards Human-Level Quality Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 87

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T04:09:34.569355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-26T17:12:38.192534Z digest=sha256:20a158a402943581611481349edc9ee941257aa0657030226064eb6964804546

Observation d0a5a82c-7fae-4054-b5ba-bb589f51e48e · inbound

WHERE to Generate Matters: Budget-Aware Synthetic Augmentation for Label Skewed Federated Learning cites this paper.

WHERE to Generate Matters: Budget-Aware Synthetic Augmentation for Label Skewed Federated Learning Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 23

Resolution
metadata mismatch
local_arxiv, observed 2026-07-11T01:47:47.926104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-11T01:38:16.853216Z digest=sha256:4044d76d9ea8f0964ce0663d9fea41ebcbe3ce8c9876d7850b83015127394c9d

Observation 4850f5a0-48cc-48fb-a5ed-f690ec5158f5 · inbound

Optimal Domain-Aware Privacy Mechanisms for Synthetic Data Generation cites this paper.

Optimal Domain-Aware Privacy Mechanisms for Synthetic Data Generation Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-01T16:26:23.721901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T16:26:23.721901Z digest=sha256:78761a4fff2d674822785807381930e3b3dadaff27cc975b81e56273e158c850