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Paper Citation Record · LEDGER

TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2406.19380.

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

pith.paper-citation-record.v1
2406.19380 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:15:33.298514Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T22:06:16.757809Z

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 a8a11ea9-6907-4519-98a9-d8454bc8e951 · inbound

Representation Learning for Tabular Data: A Comprehensive Survey cites this paper.

Representation Learning for Tabular Data: A Comprehensive Survey TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

Reference 109

Resolution
unresolved
no resolver link, observed 2026-08-16T12:15:33.298514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:15:33.298514Z digest=sha256:278af5fb483b4a8975fb3ba567a9e34238de99aa20d9138640b906e1eebf3398

Observation edff1b2c-199d-47a4-9273-8cdd4b6d5c23 · inbound

Make Still Further Progress: Chain of Thoughts for Tabular Data Leaderboard cites this paper.

Make Still Further Progress: Chain of Thoughts for Tabular Data Leaderboard TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-15T20:18:43.181274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:18:43.181274Z digest=sha256:47a2046ea03dd9a5732b2cd746bc279212ffbef62d88384bacf9545318dfc6da

Observation a80e8505-8013-46b2-b9fb-fbb429d484c8 · inbound

MultiTab: A Comprehensive Benchmark Suite for Multi-Dimensional Evaluation in Tabular Domains cites this paper.

MultiTab: A Comprehensive Benchmark Suite for Multi-Dimensional Evaluation in Tabular Domains TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T15:39:25.454631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:39:25.454631Z digest=sha256:64c0fa373c03f83ec58390c218731a64a8a28ae6cfd2c143af0228997dc99c08

Observation 0d204686-1935-424b-8f0a-84c159799f42 · inbound

TabArena: A Living Benchmark for Machine Learning on Tabular Data cites this paper.

TabArena: A Living Benchmark for Machine Learning on Tabular Data TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-19T08:42:12.603055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-19T08:41:35.789878Z digest=sha256:a198a992a1582363c18469fa34893410524f10df945d46306150ba6ff5f3cf25

Observation e364db2c-766b-467a-bf16-e84ccfc4460b · inbound

Ethics through the Facets of Artificial Intelligence cites this paper.

Ethics through the Facets of Artificial Intelligence TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T15:02:20.433829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:02:20.433829Z digest=sha256:30ee55a3bd41d09ea8c0a884f3cf9bf7a898d1cadb158793da21f2d1fb603781

Observation 3c8a42d4-76fa-4d4d-83e6-8d77f2469e84 · inbound

Data Language Models: A New Foundation Model Class for Tabular Data cites this paper.

Data Language Models: A New Foundation Model Class for Tabular Data TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

Reference 15

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T20:11:10.255788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-08T10:06:34.627253Z digest=sha256:ba5e985eef2e53c6e264f6a258a7b1870cb9ffa107dc79153926487419aad9ec

Observation 03a6b07f-6804-4008-b6e5-291c01a54db9 · inbound

Why SGD is not Brownian Motion: A New Perspective on Stochastic Dynamics cites this paper.

Why SGD is not Brownian Motion: A New Perspective on Stochastic Dynamics TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-05-22T08:11:17.511561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-22T08:06:52.309619Z digest=sha256:a99ccfc894150ca0458fabaad3f51e6c0d5043372bd405afb1486cdd6915ffe3

Observation 02b382f7-d581-4429-b37e-6b7e3a082fb4 · inbound

TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks cites this paper.

TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-07-01T22:06:16.759834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-28T15:43:46.621365Z digest=sha256:bbba0873d33295af26d2a610cb9bb6a23960976d51691c2a23ebf0116d67aef2

Observation ae0a23ea-f214-44e5-9b51-7df635035e10 · inbound

Beyond IID: How General Are Tabular Foundation Models, Really? cites this paper.

Beyond IID: How General Are Tabular Foundation Models, Really? TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-06-30T07:04:21.409584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-30T06:59:14.626274Z digest=sha256:4e760098392ec3acf679b45ff5fd720488150fbc704fb551ace0ae9dbb4abf32