Paper Citation Record · LEDGER

AMLB: an AutoML Benchmark

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2207.12560.

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

pith.paper-citation-record.v1
2207.12560 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 2026-08-14T06:32:32.682623+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:32:53.880682Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T20:03:43.690605Z

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 929e744e-1ffc-490f-92db-ff55a189093a · inbound

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data cites this paper.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data AMLB: an AutoML Benchmark

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.880682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b74c694-9d70-4a54-aabc-1fdda53cc4f6 · inbound

Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data cites this paper.

Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data AMLB: an AutoML Benchmark

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T20:02:22.715909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

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

Reference 8

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d804d3ba-5ce6-4287-8a5a-51fc6a3d7f73 · inbound

AGOP-IxG: A Gradient Covariance Filter for Local Feature Attribution on Tabular Data, with a Controlled Benchmark cites this paper.

AGOP-IxG: A Gradient Covariance Filter for Local Feature Attribution on Tabular Data, with a Controlled Benchmark AMLB: an AutoML Benchmark

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-20T20:03:43.693581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.