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Paper Citation Record · LEDGER

Generating Realistic Tabular Data with Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.21717.

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

pith.paper-citation-record.v1
2410.21717 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 2026-08-06T17:43:53.776191Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:43:54.900862Z

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 411cf88c-91f2-4b78-bae0-ea74c6dfa550 · inbound

Towards High Supervised Learning Utility Training Data Generation: Data Pruning and Column Reordering cites this paper.

Towards High Supervised Learning Utility Training Data Generation: Data Pruning and Column Reordering Generating Realistic Tabular Data with Large Language Models

Reference 41

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T17:43:54.905399Z

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=2026-08-06T17:43:53.776191Z digest=sha256:eaea0591bbf0f807be35b17d61e821ea79976d04da91923a6a9783059321753c

Observation a4ecad71-ddfa-4975-81eb-05050470bcda · inbound

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data cites this paper.

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data Generating Realistic Tabular Data with Large Language Models

Reference 162

Resolution
unresolved
no resolver link, observed 2026-08-03T08:15:27.096697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T08:15:27.096697Z digest=sha256:4e8d53dd0912a1387e4bcf759765c77fe1912854b9bd62fb4523b5cb8d7e2a48