Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Diffusion Models for Tabular Data Imputation and Synthetic Data Generation
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2407.02549.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T05:13:50.244361Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T08:05:31.274715Z
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 56c70c32-b6a1-4f4a-8a01-6f232292a81d · inbound
Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries cites this paper.
Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Diffusion Models for Tabular Data Imputation and Synthetic Data Generation
Reference 68
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T05:13:50.244361Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1114ef7-6f71-409a-8382-99481ffe6ca2 · inbound
TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data cites this paper.
TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data Diffusion Models for Tabular Data Imputation and Synthetic Data Generation
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:41:47.698954Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5243d471-3225-4ee5-9432-b371f0aa2d0e · inbound
Diffusion and Flow Matching Models for Tabular Data: A Survey cites this paper.
Diffusion and Flow Matching Models for Tabular Data: A Survey Diffusion Models for Tabular Data Imputation and Synthetic Data Generation
Reference 115
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T08:05:31.277424Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 502cb3f2-68ea-40e6-a13e-95df227a6c9a · inbound
Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN cites this paper.
Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN Diffusion Models for Tabular Data Imputation and Synthetic Data Generation
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:42:45.336335Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ceab8fd3-9534-4692-8234-31a873889e26 · inbound
Repurposing Image Diffusion Models for Adversarial Synthetic Structured Data: A Case Study of Ground Truth Drift cites this paper.
Repurposing Image Diffusion Models for Adversarial Synthetic Structured Data: A Case Study of Ground Truth Drift Diffusion Models for Tabular Data Imputation and Synthetic Data Generation
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T15:56:35.597348Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.