Paper Citation Record · LEDGER

OpenML Benchmarking Suites

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:1708.03731.

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

pith.paper-citation-record.v1
1708.03731 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 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 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:23:06.127733Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T07:16:45.137211Z

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 664de5a2-19e5-425e-af16-71b69ad7383a · inbound

Two-stage Optimization for Machine Learning Workflow cites this paper.

Two-stage Optimization for Machine Learning Workflow OpenML Benchmarking Suites

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-25T12:30:48.002348Z

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 a493816b-54b2-4d86-9808-6e3121e67d7c · inbound

TabFlex: Scaling Tabular Learning to Millions with Linear Attention cites this paper.

TabFlex: Scaling Tabular Learning to Millions with Linear Attention OpenML Benchmarking Suites

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T10:23:06.127733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e19336a5-63fb-4501-933e-a9dcfb51078b · inbound

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

TabArena: A Living Benchmark for Machine Learning on Tabular Data OpenML Benchmarking Suites

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-19T08:42:12.674704Z

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 e6fd2e48-71af-495a-89f6-08793036b644 · inbound

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning cites this paper.

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning OpenML Benchmarking Suites

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T22:44:04.015420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Towards Benchmarking Foundation Models for Tabular Data With Text cites this paper.

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

Reference 2

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3db2987-9a5b-4d00-b15d-973f843f187a · inbound

Meta-learning ecological priors from large language models explains human learning and decision making cites this paper.

Meta-learning ecological priors from large language models explains human learning and decision making OpenML Benchmarking Suites

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T14:46:34.754125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02d0cc00-863d-48a4-b3d5-a372746f436e · inbound

PIPES: A Meta-dataset of Machine Learning Pipelines cites this paper.

PIPES: A Meta-dataset of Machine Learning Pipelines OpenML Benchmarking Suites

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T19:01:47.631929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9d5915b-0001-4353-bd84-04689a1683ca · inbound

MacrOData: New Benchmarks of Thousands of Datasets for Tabular Outlier Detection cites this paper.

MacrOData: New Benchmarks of Thousands of Datasets for Tabular Outlier Detection OpenML Benchmarking Suites

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-16T06:10:40.782820Z

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 9f5102ea-035a-4d99-8d45-f73edfb33856 · inbound

Prior-Aligned Data Cleaning for Tabular Foundation Models cites this paper.

Prior-Aligned Data Cleaning for Tabular Foundation Models OpenML Benchmarking Suites

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:31:16.984098Z

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 a0532af9-8b2e-47c4-85d9-22aed05fe2ad · inbound

Mitigating Label Shift in Tabular In-Context Learning via Test-Time Posterior Adjustment cites this paper.

Mitigating Label Shift in Tabular In-Context Learning via Test-Time Posterior Adjustment OpenML Benchmarking Suites

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:25:44.734547Z

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 b851edad-191e-4ddf-9172-1990e6305ed7 · inbound

Mitigating Label Shift in Tabular In-Context Learning via Test-Time Posterior Adjustment cites this paper.

Mitigating Label Shift in Tabular In-Context Learning via Test-Time Posterior Adjustment OpenML Benchmarking Suites

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-01T00:35:10.304614Z

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 6efbe4f1-8116-4c26-a146-8e2530a14680 · inbound

TabEmbed: Benchmarking and Learning Generalist Embeddings for Tabular Understanding cites this paper.

TabEmbed: Benchmarking and Learning Generalist Embeddings for Tabular Understanding OpenML Benchmarking Suites

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:21:06.674875Z

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 d9f7d542-d32a-4284-974a-2e27c3a88c38 · 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 OpenML Benchmarking Suites

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T20:11:10.263025Z

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 d026bb8a-e8d9-499b-8d71-4a299e1daa87 · inbound

Active Tabular Augmentation via Policy-Guided Diffusion Inpainting cites this paper.

Active Tabular Augmentation via Policy-Guided Diffusion Inpainting OpenML Benchmarking Suites

Reference 59

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T03:56:21.785077Z

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 3cf7bdd3-bd22-4388-8403-ebc30b329e68 · inbound

Shaping the Prior: How Synthetic Task Distributions Determine Tabular Foundation Model Quality cites this paper.

Shaping the Prior: How Synthetic Task Distributions Determine Tabular Foundation Model Quality OpenML Benchmarking Suites

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T12:43:17.590660Z

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 fb567317-78a2-4a2e-ade3-39deb8866a68 · inbound

Ternary Decision Trees with Locally-Adaptive Uncertainty Zones cites this paper.

Ternary Decision Trees with Locally-Adaptive Uncertainty Zones OpenML Benchmarking Suites

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T07:11:12.508327Z

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 7717e52b-2453-4fbe-bd88-0e93a388f390 · inbound

Ternary Decision Trees with Locally-Adaptive Uncertainty Zones cites this paper.

Ternary Decision Trees with Locally-Adaptive Uncertainty Zones OpenML Benchmarking Suites

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T16:54:58.647795Z

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 9e253e1f-0b93-4513-a08a-1a5220ab2502 · inbound

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

TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks OpenML Benchmarking Suites

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-01T22:06:16.775233Z

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 388c6986-2ae6-4a97-9b3c-1241e8fe9476 · inbound

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models cites this paper.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models OpenML Benchmarking Suites

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T07:16:45.138956Z

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 674dd40d-8c6c-45ad-9823-a410ed982052 · inbound

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

Beyond IID: How General Are Tabular Foundation Models, Really? OpenML Benchmarking Suites

Reference 103

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:04:21.470011Z

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.