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Paper Citation Record · LEDGER

Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2309.09968.

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

pith.paper-citation-record.v1
2309.09968 v3

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:58:15.754728Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T12:46:03.969520Z

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 8d64ed29-2b87-4b43-971f-00b7e6931997 · inbound

CFMI: Flow Matching for Missing Data Imputation cites this paper.

CFMI: Flow Matching for Missing Data Imputation Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T04:58:15.754728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:58:15.754728Z digest=sha256:e61760c327f09fc106e2ee130c09c9f5f68d9b00da27eff39dd7f9afedb2d18a

Observation f0581107-a6f4-45ec-8eab-a358d2a60b82 · inbound

Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training cites this paper.

Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees

Reference 114

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:46:03.976137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T03:04:54.146481Z digest=sha256:afe0f1a99e289da444f1c388005f5d96627e9a931788f8401b422e6240f99454