Paper Citation Record · LEDGER

Table Foundation Models: on knowledge pre-training for tabular learning

As of 8 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 6 inbound Pith citation observations for arXiv:2505.14415.

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

pith.paper-citation-record.v1
2505.14415 v2

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:38:39.465674Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:20:02.370073Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T07:04:21.323657Z

Reference resolution

27 of 27 outbound references displayed

verified exact0
verified fuzzy12
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 05daca70-f481-4555-a2b3-c152619b463d · outbound

This paper cites GPT-4 Technical Report.

Table Foundation Models: on knowledge pre-training for tabular learning GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:36.320105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2f4bf66-8f57-4a9d-96bc-e0fb19492045 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Table Foundation Models: on knowledge pre-training for tabular learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:37.045005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5b8e220-0245-46ad-a9ca-7be97b992e7a · outbound

This paper cites Koshil, T.

Table Foundation Models: on knowledge pre-training for tabular learning Koshil, T

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:41.473724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5754cf65-c4a3-43bf-9834-6b0b9260a335 · outbound

This paper cites TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems.

Table Foundation Models: on knowledge pre-training for tabular learning TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:37.539366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c996fa5-e22e-471f-8a49-d66da0a24bb8 · outbound

This paper cites Advances in Pre-Training Distributed Word Representations.

Table Foundation Models: on knowledge pre-training for tabular learning Advances in Pre-Training Distributed Word Representations

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:37.704376Z

Source-reported events for the cited work

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Observation 6b782cd1-602f-4e26-963e-d1598e0adf66 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Table Foundation Models: on knowledge pre-training for tabular learning Representation Learning with Contrastive Predictive Coding

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:37.815110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 369f8a73-20c8-45f4-b690-4e58c41bb318 · outbound

This paper cites Reimers and I.

Table Foundation Models: on knowledge pre-training for tabular learning Reimers and I

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:41.260103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7e4c48b1-9577-4006-aeaf-3d6183262aeb · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Table Foundation Models: on knowledge pre-training for tabular learning Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:38.231330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c2f275b-f1f8-4076-b79a-5488b3166a53 · outbound

This paper cites 14 KNOWLEDGE PRE -TRAINING OF TABLE FOUNDATION MODELS - SEPTEMBER 9, 2025 R.

Table Foundation Models: on knowledge pre-training for tabular learning 14 KNOWLEDGE PRE -TRAINING OF TABLE FOUNDATION MODELS - SEPTEMBER 9, 2025 R

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:41.088949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6838a05f-8b83-45f0-abb7-8bc683c618a6 · outbound

This paper cites Spinaci, M.

Table Foundation Models: on knowledge pre-training for tabular learning Spinaci, M

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:40.915967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 812f3ba6-6b66-4e7a-a2d5-f280d620f0ce · outbound

This paper cites Thomas, J.

Table Foundation Models: on knowledge pre-training for tabular learning Thomas, J

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:40.748265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0a300e75-9d49-4ec3-86e2-26831997de0b · outbound

This paper cites Hype, Sustainability, and the Price of the Bigger-is-Better Paradigm in AI.

Table Foundation Models: on knowledge pre-training for tabular learning Hype, Sustainability, and the Price of the Bigger-is-Better Paradigm in AI

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:38.702636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2a7d7e9-d8f6-491a-8a91-d5aca0cf8617 · outbound

This paper cites Ye, S.-Y.

Table Foundation Models: on knowledge pre-training for tabular learning Ye, S.-Y

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:38.960868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 859769ec-bfd1-4494-b384-107db2296c7d · outbound

This paper cites Zhang, X.

Table Foundation Models: on knowledge pre-training for tabular learning Zhang, X

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:40.590633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3fda673a-fc41-4e98-90b9-59d708ede783 · outbound

This paper cites The column information is crucial to supplement context for the transformers (Kim et al., 2024).

Table Foundation Models: on knowledge pre-training for tabular learning The column information is crucial to supplement context for the transformers (Kim et al., 2024)

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:40.388359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5fb3ed96-fdce-4bcb-bee5-73d17ef89985 · outbound

This paper cites For the runtime, it measures the total time for data preparation, hyperparameter optimization, and prediction.

Table Foundation Models: on knowledge pre-training for tabular learning For the runtime, it measures the total time for data preparation, hyperparameter optimization, and prediction

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:40.011182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 79cd26cb-4cb7-4262-926a-c1160e17d0ac · outbound

This paper cites For each baseline, some additional details were considered.

Table Foundation Models: on knowledge pre-training for tabular learning For each baseline, some additional details were considered

Reference 256

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:39.839027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ae3cbade-d8cd-4294-9b7b-82073b76ec50 · outbound

This paper cites For models without native handling missing values, we imputed with the mean for numerical features, and treated as another category for categorical features.

Table Foundation Models: on knowledge pre-training for tabular learning For models without native handling missing values, we imputed with the mean for numerical features, and treated as another category for categorical features

Reference 500

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:40.210026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 40638564-2700-44a8-a020-dc504a4023e0 · outbound

This paper cites UniPredict: Large Language Models are Universal Tabular Classifiers.

Table Foundation Models: on knowledge pre-training for tabular learning UniPredict: Large Language Models are Universal Tabular Classifiers

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:38.827416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccf32c95-9c0e-4e22-bbbf-093bb681edee · outbound

This paper cites TabICL: A Tabular Foundation Model for In-Context Learning on Large Data.

Table Foundation Models: on knowledge pre-training for tabular learning TabICL: A Tabular Foundation Model for In-Context Learning on Large Data

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:37.990674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04dfa0f8-5e58-47cc-b96c-65236f251363 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Table Foundation Models: on knowledge pre-training for tabular learning On the Opportunities and Risks of Foundation Models

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:36.578911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abacee11-92d7-4654-8e4a-4426bc68c310 · outbound

This paper cites Cross-Table Pretraining towards a Universal Function Space for Heterogeneous Tabular Data.

Table Foundation Models: on knowledge pre-training for tabular learning Cross-Table Pretraining towards a Universal Function Space for Heterogeneous Tabular Data

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:36.735423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7382e971-adee-4228-a66a-fc1a7a415593 · outbound

This paper cites 12 KNOWLEDGE PRE -TRAINING OF TABLE FOUNDATION MODELS - SEPTEMBER 9, 2025 L.

Table Foundation Models: on knowledge pre-training for tabular learning 12 KNOWLEDGE PRE -TRAINING OF TABLE FOUNDATION MODELS - SEPTEMBER 9, 2025 L

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:41.983251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7cc20e83-7ade-40a9-ae58-01cf800dbc2d · outbound

This paper cites TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks.

Table Foundation Models: on knowledge pre-training for tabular learning TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:36.978304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1b7c798-9836-4d1c-8fb0-e8765b32c604 · outbound

This paper cites Herzig, T.

Table Foundation Models: on knowledge pre-training for tabular learning Herzig, T

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:41.679330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6b40c6c7-0223-421a-9c73-3418f3ae3131 · outbound

This paper cites Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers.

Table Foundation Models: on knowledge pre-training for tabular learning Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:36.898481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f910b30-ae96-41ed-923f-204d60c466ca · outbound

This paper cites Better by Default: Strong Pre-Tuned MLPs and Boosted Trees on Tabular Data.

Table Foundation Models: on knowledge pre-training for tabular learning Better by Default: Strong Pre-Tuned MLPs and Boosted Trees on Tabular Data

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:37.319197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 48d2a58e-7701-44fd-a6bd-4891431660d6 · inbound

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models cites this paper.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Table Foundation Models: on knowledge pre-training for tabular learning

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:02.370073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d38ef5f4-dcb3-4971-8352-f661fb003b97 · inbound

Universal Embeddings of Tabular Data cites this paper.

Universal Embeddings of Tabular Data Table Foundation Models: on knowledge pre-training for tabular learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T19:19:59.589569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2314dd8a-fbf9-4352-a56f-abd27e69907b · inbound

No Data? No Problem: Robust Vision-Tabular Learning with Missing Values cites this paper.

No Data? No Problem: Robust Vision-Tabular Learning with Missing Values Table Foundation Models: on knowledge pre-training for tabular learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T14:45:18.771139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1577594e-4499-4b24-80e0-646c96ccf321 · inbound

RamanBench: A Large-Scale Benchmark for Machine Learning on Raman Spectroscopy cites this paper.

RamanBench: A Large-Scale Benchmark for Machine Learning on Raman Spectroscopy Table Foundation Models: on knowledge pre-training for tabular learning

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:21:07.886717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9efba0da-0413-42e0-9d99-05436f1b14b7 · inbound

MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image cites this paper.

MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image Table Foundation Models: on knowledge pre-training for tabular learning

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:51:25.033687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 46208e56-f6a2-42b8-8eb5-68e868d71d9f · inbound

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

Beyond IID: How General Are Tabular Foundation Models, Really? Table Foundation Models: on knowledge pre-training for tabular learning

Reference 119

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:04:21.325344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.