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Paper Citation Record · LEDGER

Towards Benchmarking Foundation Models for Tabular Data With Text

As of 9 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 3 inbound Pith citation observations for arXiv:2507.07829.

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

pith.paper-citation-record.v1
2507.07829 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:36:47.958225Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T07:34:47.760875Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T08:04:29.090042Z

Reference resolution

26 of 26 outbound references displayed

  • verified exact0
  • verified fuzzy2
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1c7d4019-78e6-4a09-b12b-428e12e41c91 · outbound

This paper cites write newline.

Towards Benchmarking Foundation Models for Tabular Data With Text write newline

Reference 1

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unresolved
no resolver link, observed 2026-08-06T18:36:46.629336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:36:46.629336Z digest=sha256:61f42ed96ce025e645fa2f673985e74ede4f24e8379d81eeab2ffb3dc5dc00f0

Observation baf2414d-065f-4a50-a179-fcdb89fd3b6b · outbound

This paper cites OpenML Benchmarking Suites.

Towards Benchmarking Foundation Models for Tabular Data With Text OpenML Benchmarking Suites

Reference 2

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no resolver link, observed 2026-08-06T18:36:46.741921Z

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source=arxiv_source observed=2026-08-06T18:36:46.741921Z digest=sha256:72e06874dbade231b802acd27e92c69a603cc1f3070169c5f192c681aedd2f78

Observation 377f81f8-07a2-4e19-8c55-b165bf9a981d · outbound

This paper cites Enriching Word Vectors with Subword Information.

Towards Benchmarking Foundation Models for Tabular Data With Text Enriching Word Vectors with Subword Information

Reference 3

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no resolver link, observed 2026-08-06T18:36:46.868838Z

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source=arxiv_source observed=2026-08-06T18:36:46.868838Z digest=sha256:180de63e6078f6a432aa414ce16914a9f7a388f167e4bc20edcb18716e207eae

Observation 483d32a2-ff1e-4cbd-a28b-b3533f925e72 · outbound

This paper cites V., Na, L., Ma, Y., Boussioux, L., Zeng, C., Soenksen, L.

Towards Benchmarking Foundation Models for Tabular Data With Text V., Na, L., Ma, Y., Boussioux, L., Zeng, C., Soenksen, L

Reference 4

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no resolver link, observed 2026-08-06T18:36:47.052197Z

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source=arxiv_source observed=2026-08-06T18:36:47.052197Z digest=sha256:45ff275bfdd7ad5a6292ebbf542b0423eec0dc6f50367755bc47a9e1ca019567

Observation 877e9463-acaa-49d1-abe0-80df7238f766 · outbound

This paper cites and Guestrin, C.

Towards Benchmarking Foundation Models for Tabular Data With Text and Guestrin, C

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-06T18:36:48.592767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation da1cfbfd-2367-4aa7-b9d3-abe8e32e0193 · outbound

This paper cites AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data.

Towards Benchmarking Foundation Models for Tabular Data With Text AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

Reference 7

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no resolver link, observed 2026-08-06T18:36:47.379543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:36:47.379543Z digest=sha256:4b61f5a73dad5b95caa2def95f64aafff45f5ecf2df0e2b1eedc3d036aba83d6

Observation fd806105-fa00-42c0-8498-182df74f00b6 · outbound

This paper cites AMLB: an AutoML Benchmark.

Towards Benchmarking Foundation Models for Tabular Data With Text AMLB: an AutoML Benchmark

Reference 8

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no resolver link, observed 2026-08-06T18:36:47.491670Z

Source-reported events for the cited work

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Observation bacee3e0-ffd2-49d5-a053-b5645203fb63 · outbound

This paper cites L., Amaral, L.

Towards Benchmarking Foundation Models for Tabular Data With Text L., Amaral, L

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-06T18:36:48.572115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:36:47.546239Z digest=sha256:fe6eb949d052b0c31f755b87415e8d159e35be7799c1a91ce398ab3ef556228e

Observation 397e6b2c-c2bc-48c7-9a81-fad9763d348b · outbound

This paper cites Vectorizing string entries for data processing on tables: when are larger language models better?.

Towards Benchmarking Foundation Models for Tabular Data With Text Vectorizing string entries for data processing on tables: when are larger language models better?

Reference 10

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no resolver link, observed 2026-08-06T18:36:47.624023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 553da31f-b73a-417e-bc29-3f3a0fffff2d · outbound

This paper cites TabLLM: Few-shot Classification of Tabular Data with Large Language Models.

Towards Benchmarking Foundation Models for Tabular Data With Text TabLLM: Few-shot Classification of Tabular Data with Large Language Models

Reference 11

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no resolver link, observed 2026-08-06T18:36:47.741196Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:36:47.741196Z digest=sha256:9b156c39122b755d5daae0c29300319005e078e5fedc30b4d56082c3f9f36d4e

Observation 2a0e2f26-28a3-4db7-99dd-1e2047a4d95b · outbound

This paper cites Machine Learning for Health symposium 2023 -- Findings track.

Towards Benchmarking Foundation Models for Tabular Data With Text Machine Learning for Health symposium 2023 -- Findings track

Reference 12

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metadata mismatch
local_arxiv, observed 2026-08-06T18:36:48.343264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:36:47.771782Z digest=sha256:0bf165ced7ce56811d0aec117cbe4ae8944ce7576e3fde195d759bc5a014175a

Observation 3d999283-7563-4363-a603-ddc2a8712cc4 · outbound

This paper cites u ller, S., Purucker, L., Krishnakumar, A., K \.

Towards Benchmarking Foundation Models for Tabular Data With Text u ller, S., Purucker, L., Krishnakumar, A., K \

Reference 13

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no resolver link, observed 2026-08-06T18:36:47.776363Z

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Unavailable: canonical work link unavailable.

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Observation 2f229c0d-7b38-45e0-871a-c7df06729364 · outbound

This paper cites CARTE: Pretraining and Transfer for Tabular Learning.

Towards Benchmarking Foundation Models for Tabular Data With Text CARTE: Pretraining and Transfer for Tabular Learning

Reference 14

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Observation 4cfe51fd-5639-4fb0-b60c-704ef2f0020a · outbound

This paper cites LLM Embeddings for Deep Learning on Tabular Data.

Towards Benchmarking Foundation Models for Tabular Data With Text LLM Embeddings for Deep Learning on Tabular Data

Reference 15

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no resolver link, observed 2026-08-06T18:36:47.785860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f2b6bb55-8deb-414c-8e46-6085c0fd301d · outbound

This paper cites TALENT: A Tabular Analytics and Learning Toolbox.

Towards Benchmarking Foundation Models for Tabular Data With Text TALENT: A Tabular Analytics and Learning Toolbox

Reference 16

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no resolver link, observed 2026-08-06T18:36:47.790726Z

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Observation d212f918-239c-42a2-a6cb-30ab6f33bb59 · outbound

This paper cites Mug: A multimodal classification benchmark on game data with tabular, textual, and visual fields.

Towards Benchmarking Foundation Models for Tabular Data With Text Mug: A multimodal classification benchmark on game data with tabular, textual, and visual fields

Reference 17

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unresolved
no resolver link, observed 2026-08-06T18:36:47.796759Z

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source=arxiv_source observed=2026-08-06T18:36:47.796759Z digest=sha256:871cede61f88ed6069fd29d0d2728fe545871e8e004c482484f8604c5466def0

Observation 0e193bd7-f170-4e32-afac-bd6d0fee7595 · outbound

This paper cites an unresolved cited work.

Towards Benchmarking Foundation Models for Tabular Data With Text Unresolved cited work

Reference 18

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no resolver link, observed 2026-08-06T18:36:47.801181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:36:47.801181Z digest=sha256:85b9fafe2b17bc2908038e19310b592d0bd625e69fba8fcd1b1f4f6037c549e7

Observation dd1bc50d-5e66-4035-9d14-95163b290aee · outbound

This paper cites C., Golestan, K., Yu, G., Volkovs, M., and Caterini, A.

Towards Benchmarking Foundation Models for Tabular Data With Text C., Golestan, K., Yu, G., Volkovs, M., and Caterini, A

Reference 19

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no resolver link, observed 2026-08-06T18:36:47.805612Z

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Observation de99a1bf-5ee9-4548-b326-cb14bf0be713 · outbound

This paper cites and Ratajczak, W.

Towards Benchmarking Foundation Models for Tabular Data With Text and Ratajczak, W

Reference 20

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no resolver link, observed 2026-08-06T18:36:47.923586Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:36:47.923586Z digest=sha256:e2d58b1c7baaf05645c29f691a63e81ace3cd85f7a2d63477e5fe8b6f528fc80

Observation b77ceb41-ea15-4e30-a9a0-62a0e3e34b3d · outbound

This paper cites an unresolved cited work.

Towards Benchmarking Foundation Models for Tabular Data With Text Unresolved cited work

Reference 21

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unresolved
raw_fallback, observed 2026-08-06T18:36:48.542595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:36:47.928885Z digest=sha256:71382dd4e0844dccef789ed44cc8c2d465f891bc98d422254af2d7902a01ac0d

Observation 3c40f97a-7d09-4260-87f3-95a17bc30202 · outbound

This paper cites When Do Neural Nets Outperform Boosted Trees on Tabular Data?.

Towards Benchmarking Foundation Models for Tabular Data With Text When Do Neural Nets Outperform Boosted Trees on Tabular Data?

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 20f4a16d-b51d-445d-b8e4-85069cf05237 · outbound

This paper cites Benchmarking Multimodal AutoML for Tabular Data with Text Fields.

Towards Benchmarking Foundation Models for Tabular Data With Text Benchmarking Multimodal AutoML for Tabular Data with Text Fields

Reference 23

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no resolver link, observed 2026-08-06T18:36:47.938962Z

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source=arxiv_source observed=2026-08-06T18:36:47.938962Z digest=sha256:86abbe5ba2c74514740892f79f485145a1e5a7d81089bd347e2b9a38722eb837

Observation 68150fff-f389-4666-be6f-8c868c976331 · outbound

This paper cites JoLT: Joint Probabilistic Predictions on Tabular Data Using LLMs.

Towards Benchmarking Foundation Models for Tabular Data With Text JoLT: Joint Probabilistic Predictions on Tabular Data Using LLMs

Reference 24

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no resolver link, observed 2026-08-06T18:36:47.943525Z

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source=arxiv_source observed=2026-08-06T18:36:47.943525Z digest=sha256:f58ebfb801f15f532cb2732c5ebaf7f75d66392033ccb718571db3c6c70b4b8b

Observation b7cd1408-79a6-4cfc-98cf-5c62396afbdd · outbound

This paper cites AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models.

Towards Benchmarking Foundation Models for Tabular Data With Text AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models

Reference 25

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no resolver link, observed 2026-08-06T18:36:47.948093Z

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source=arxiv_source observed=2026-08-06T18:36:47.948093Z digest=sha256:d9586e59c23389461a3d2dbaeb44b4c0b6747d9ed0c968c18854386225ad3b9a

Observation 39807671-9e31-42b6-b726-dd81eba8cd87 · outbound

This paper cites MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers.

Towards Benchmarking Foundation Models for Tabular Data With Text MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers

Reference 26

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unresolved
no resolver link, observed 2026-08-06T18:36:47.952726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:36:47.952726Z digest=sha256:0076f12086b38a3ee9bf2d8b4b7cc0c3668a1a0e142de928ce6029586350d470

Observation df858277-3b94-4495-b64a-1bbc205d457e · outbound

This paper cites TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios.

Towards Benchmarking Foundation Models for Tabular Data With Text TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios

Reference 27

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unresolved
no resolver link, observed 2026-08-06T18:36:47.958225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:36:47.958225Z digest=sha256:6b2ecb6043a6aad2f2d709d352b0892b063d6006afbda7574e9c55c63d3d9a25

Pith citing papers

Observation 036e564d-2896-4d9d-a8c4-e74202eb4aa7 · inbound

STRABLE: Benchmarking Tabular Machine Learning with Strings cites this paper.

STRABLE: Benchmarking Tabular Machine Learning with Strings Towards Benchmarking Foundation Models for Tabular Data With Text

Reference 42

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verified exact
arxiv_id, observed 2026-05-13T05:17:18.441754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T05:13:15.039160Z digest=sha256:798962e4cf02e536a595010da88db63475f85b13b6efca501527c56261fe6a36

Observation 378dff40-5ec7-4857-906e-3d4ce8efecff · inbound

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

Beyond IID: How General Are Tabular Foundation Models, Really? Towards Benchmarking Foundation Models for Tabular Data With Text

Reference 16

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verified exact
arxiv_id, observed 2026-06-30T07:04:21.420092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T06:59:14.626274Z digest=sha256:ede3f45bf1886cdf27128b0e1d22c61f947d688fb339a3ab5e26bfa827ed2b90

Observation 4a372cec-af06-47c5-9513-4821a51dd7f5 · inbound

Exploring Differences Between Tabular Enterprise Data and Public Benchmarks cites this paper.

Exploring Differences Between Tabular Enterprise Data and Public Benchmarks Towards Benchmarking Foundation Models for Tabular Data With Text

Reference 10

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metadata mismatch
arxiv_id, observed 2026-06-30T08:04:29.091444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-30T07:34:47.760875Z digest=sha256:6a86db9db95c3cd0cfab5672e8970c627be09c7ee5952b3e940dda64491feef3