Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Relational Data Synthesis using Generative Adversarial Networks: A Design Space Exploration
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2008.12763.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T05:02:17.514910Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T19:07:26.890711Z
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 04ba20bc-7885-460f-bc93-6e0c3661a86b · inbound
A Systematic Evaluation of Generative Models on Tabular Transportation Data cites this paper.
A Systematic Evaluation of Generative Models on Tabular Transportation Data Relational Data Synthesis using Generative Adversarial Networks: A Design Space Exploration
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:30:45.195928Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b616f2cb-93d1-4a69-bb60-2bc872f3ee25 · inbound
RIPOST: Two-Phase Private Decomposition for Multidimensional Data cites this paper.
RIPOST: Two-Phase Private Decomposition for Multidimensional Data Relational Data Synthesis using Generative Adversarial Networks: A Design Space Exploration
Reference 2020
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-07T19:07:26.899378Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation acd80137-8ab6-4307-9957-7b492d0a24e7 · inbound
Quantitative Auditing of AI Fairness with Differentially Private Synthetic Data cites this paper.
Quantitative Auditing of AI Fairness with Differentially Private Synthetic Data Relational Data Synthesis using Generative Adversarial Networks: A Design Space Exploration
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T05:02:17.514910Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.