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Paper Citation Record · LEDGER

Sequential Models in the Synthetic Data Vault

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2207.14406.

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

pith.paper-citation-record.v1
2207.14406 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T10:46:52.161478Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T00:49:48.682493Z

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 131c3f09-697f-4074-a2a6-eeb84ae3c503 · inbound

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling cites this paper.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Sequential Models in the Synthetic Data Vault

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-08T10:46:52.161478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:46:52.161478Z digest=sha256:9a1802c9a0c02804b909bbdd094e9882bbc6299fd222b5eb47dda3eea763d278

Observation 6318da3c-ace6-4841-b845-0f04a21b34fd · inbound

Synthetic Data in Education: Empirical Insights from Traditional Resampling and Deep Generative Models cites this paper.

Synthetic Data in Education: Empirical Insights from Traditional Resampling and Deep Generative Models Sequential Models in the Synthetic Data Vault

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:49:48.683850Z

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.

source=pdf_text observed=2026-05-10T00:46:26.349406Z digest=sha256:afbee567c93b6540ad1747faa998c6a0295b8b950aad39b23e12b209ed5f4d69

Observation a06c0284-52e5-4b01-b8c4-56720f7debcf · inbound

Do Generative Models Keep Time? A Time-Aware Evaluation of Synthetic Sequential Tabular Data cites this paper.

Do Generative Models Keep Time? A Time-Aware Evaluation of Synthetic Sequential Tabular Data Sequential Models in the Synthetic Data Vault

Reference 33

Resolution
malformed identifier
no resolver link, observed 2026-08-01T22:52:41.419817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:52:41.419817Z digest=sha256:437c076112a3f50fabb4f8bb307568fcbccf67d6ed91e976e35ead4d3212955f