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Paper Citation Record · LEDGER

Unmasking Trees for Tabular Data

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.05593.

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

pith.paper-citation-record.v1
2407.05593 v5

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 2026-08-21T06:32:19.484+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:36:51.720725Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T22:42:45.908864Z

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 845137bc-f6fd-45b5-9293-cfb4ad195022 · inbound

TabTreeFormer: Tabular Data Generation Using Hybrid Tree-Transformer cites this paper.

TabTreeFormer: Tabular Data Generation Using Hybrid Tree-Transformer Unmasking Trees for Tabular Data

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-10T22:36:51.720725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:36:51.720725Z digest=sha256:6846e313577cd1d03e207ee418f7de8cced28dc50259e9be586514312cbdbdaa

Observation f38cbc97-6587-405f-ab86-4ba7006e0344 · 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 Unmasking Trees for Tabular Data

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T17:41:47.600920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:41:47.600920Z digest=sha256:cac4894d7135c634a5a0449b6aa3a2cb2b53c282cff4e55a6dbff445bea3c361

Observation 46db6027-69ea-4738-80fa-c4ef5450248e · inbound

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

Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN Unmasking Trees for Tabular Data

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-05T22:42:45.913881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T22:42:44.429740Z digest=sha256:d0b69beb5071c5978e129d598298f70e59a51867668286f78f4fbb8739086ee0