Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
OpenML: networked science in machine learning
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1407.7722.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T11:32:54.201937Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T13:39:03.732525Z
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 712d444a-50f7-4db1-95af-27b7408d5386 · 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 OpenML: networked science in machine learning
Reference 83
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:32:54.201937Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bd5ab10d-4b16-43f1-986b-36f046aa5625 · inbound
VisTabNet: Adapting Vision Transformers for Tabular Data cites this paper.
VisTabNet: Adapting Vision Transformers for Tabular Data OpenML: networked science in machine learning
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:34:13.714469Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8a21253d-1fbe-43c4-a319-8645709af745 · inbound
BOASF: A Unified Framework for Speeding up Automatic Machine Learning via Adaptive Successive Filtering cites this paper.
BOASF: A Unified Framework for Speeding up Automatic Machine Learning via Adaptive Successive Filtering OpenML: networked science in machine learning
Reference 26
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T13:39:03.831296Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.