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Paper Citation Record · LEDGER

UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2307.09249.

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

pith.paper-citation-record.v1
2307.09249 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:33:20.183217Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T05:31:33.724502Z

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 23afc3fc-5960-4d47-92ed-c1238571d83e · inbound

CACTI: Leveraging Copy Masking and Contextual Information to Improve Tabular Data Imputation cites this paper.

CACTI: Leveraging Copy Masking and Contextual Information to Improve Tabular Data Imputation UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T11:33:20.183217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:33:20.183217Z digest=sha256:e04169fd601c77b4b88988471524a7f05be96e7f8462a977b7cca8a904f07065

Observation 352659aa-af13-4112-97d6-0da7f7d73e01 · inbound

MIRRAMS: Learning Robust Tabular Models under Unseen Missingness Shifts cites this paper.

MIRRAMS: Learning Robust Tabular Models under Unseen Missingness Shifts UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T18:31:52.856693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:31:52.856693Z digest=sha256:873a903d150c27a1fdda59c80b6ba982dd580bccc902d83936fe36a32db0b89b

Observation 0fc7af22-d5b5-4e62-b488-ecbf0d9befef · inbound

Utilizing Training Data to Improve LLM Reasoning for Tabular Understanding cites this paper.

Utilizing Training Data to Improve LLM Reasoning for Tabular Understanding UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-05T16:22:50.897110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:22:50.897110Z digest=sha256:ffd109526c4623aa229461a2f89f8d42c83a2c3fc38d45beaefcd7d1f66bb213

Observation 6b06de3f-1374-4b10-933a-00877f25d270 · inbound

TREASURE: The Visa Payment Foundation Model for High-Volume Transaction Understanding cites this paper.

TREASURE: The Visa Payment Foundation Model for High-Volume Transaction Understanding UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-17T05:31:33.727100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-17T05:29:13.059403Z digest=sha256:9cf26694514d8310cb5e4bcafe675fb3214f134ddb123da7d3c1ff8b7f02c8c2