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Paper Citation Record · LEDGER

Composable Generative Models

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2102.09249.

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

pith.paper-citation-record.v1
2102.09249 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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:41:47.577271Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T22:42:45.945892Z

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 720806bb-67ae-4cd9-8e02-9fb459ae3bc5 · 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 Composable Generative Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-10T17:41:47.577271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:41:47.577271Z digest=sha256:a5e90615f0be745bf58bfd0659d291bf619eb54bb73ba58db80da036e41c48c5

Observation 3de0ef3f-fb53-4329-8501-b6c379660748 · inbound

Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN cites this paper.

Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN Composable Generative Models

Reference 32

Resolution
verified exact
local_arxiv, observed 2026-08-05T22:42:45.950398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T22:42:44.035597Z digest=sha256:b1243fcf1aa5cb47a7ac1f463bc7b235757598e0e676440c92170862bbf98f78