Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
DP-LDMs: Differentially Private Latent Diffusion Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2305.15759.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:12:17.051778Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T13:38:19.389012Z
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 a1b2cf05-69c3-4cc1-aee1-c23a2fad6ae0 · inbound
SoK: Can Synthetic Images Replace Real Data? A Survey of Utility and Privacy of Synthetic Image Generation cites this paper.
SoK: Can Synthetic Images Replace Real Data? A Survey of Utility and Privacy of Synthetic Image Generation DP-LDMs: Differentially Private Latent Diffusion Models
Reference 73
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:12:17.051778Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b7511a60-a1d4-4199-9544-10389ab7519e · inbound
Implementing Adaptations for Vision AutoRegressive Model cites this paper.
Implementing Adaptations for Vision AutoRegressive Model DP-LDMs: Differentially Private Latent Diffusion Models
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:12:33.883885Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6786ad85-9478-42d6-8dc8-a75a6faef115 · 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 DP-LDMs: Differentially Private Latent Diffusion Models
Reference 147
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T18:52:59.338788Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fce0298e-92fa-422e-8036-6d253a2e9a59 · inbound
DP-SelFT: Differentially Private Selective Fine-Tuning for Large Language Models cites this paper.
DP-SelFT: Differentially Private Selective Fine-Tuning for Large Language Models DP-LDMs: Differentially Private Latent Diffusion Models
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T13:38:19.390439Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 166156b2-a7bf-4976-a27d-f129e00a2840 · inbound
Scalable Differentially Private Data Compression via Diffusion and Stochastic Codes cites this paper.
Scalable Differentially Private Data Compression via Diffusion and Stochastic Codes DP-LDMs: Differentially Private Latent Diffusion Models
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T02:50:28.619370Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.