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Paper Citation Record · LEDGER

Scaling While Privacy Preserving: A Comprehensive Synthetic Tabular Data Generation and Evaluation in Learning Analytics

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.06883.

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

pith.paper-citation-record.v1
2401.06883 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:32:58.048307Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T21:10:38.534188Z

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 b01484c6-43ac-4c80-8b19-554855c9c84a · inbound

Ensembling Membership Inference Attacks Against Tabular Generative Models cites this paper.

Ensembling Membership Inference Attacks Against Tabular Generative Models Scaling While Privacy Preserving: A Comprehensive Synthetic Tabular Data Generation and Evaluation in Learning Analytics

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T11:32:58.048307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:32:58.048307Z digest=sha256:086b984512d248b9a8237956f22eae577c03e0018ce28c5e7fcb8d72affa30b7

Observation 27fc9223-a936-44be-826b-89c0d3e2bafb · inbound

Quality Degradation Attack in Synthetic Data cites this paper.

Quality Degradation Attack in Synthetic Data Scaling While Privacy Preserving: A Comprehensive Synthetic Tabular Data Generation and Evaluation in Learning Analytics

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-21T21:10:38.535931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T21:10:05.466845Z digest=sha256:7cf2bb0f17040462957dcb75a88b4af29dcdbfc48dc64d5f24452601c5cc5802