Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2408.14817.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:39:25.352617Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T21:10:09.616779Z
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 3bd762aa-b54c-46b3-8e65-df212e08b52a · inbound
MultiTab: A Comprehensive Benchmark Suite for Multi-Dimensional Evaluation in Tabular Domains cites this paper.
MultiTab: A Comprehensive Benchmark Suite for Multi-Dimensional Evaluation in Tabular Domains A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:39:25.352617Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation efeeb0e1-ac2e-444a-9042-e84365c61e92 · inbound
TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks cites this paper.
TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T22:06:16.762673Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 1212bb6a-cb0b-4e23-91eb-6c438bfc67dc · inbound
Clutch: High Performance Vector-Scalar Comparison using DRAM via Chunked Temporal Coding cites this paper.
Clutch: High Performance Vector-Scalar Comparison using DRAM via Chunked Temporal Coding A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
Reference 179
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T12:39:48.801279Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation b8852c06-8a51-44a8-afc6-5823b2d04bcd · inbound
Hierarchical Graph Learning for Calendar Spread Strategies in Commodity Futures Markets cites this paper.
Hierarchical Graph Learning for Calendar Spread Strategies in Commodity Futures Markets A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T21:10:09.619230Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation d080c477-db49-47f7-a354-b88eb917b82a · inbound
Beyond IID: How General Are Tabular Foundation Models, Really? cites this paper.
Beyond IID: How General Are Tabular Foundation Models, Really? A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
Reference 93
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T07:04:21.495158Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.