Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Large Language Models Engineer Too Many Simple Features For Tabular Data
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.17787.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T05:14:57.273950Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T22:06:16.794372Z
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 dd451fcd-9cff-4859-81de-e6bb427da70b · inbound
LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers cites this paper.
LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers Large Language Models Engineer Too Many Simple Features For Tabular Data
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T23:37:15.449535Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 2c509e3b-0669-437d-8e29-4d67c2ed2c93 · inbound
LLM-ML Teaming: Integrated Symbolic Decoding and Gradient Search for Valid and Stable Generative Feature Transformation cites this paper.
LLM-ML Teaming: Integrated Symbolic Decoding and Gradient Search for Valid and Stable Generative Feature Transformation Large Language Models Engineer Too Many Simple Features For Tabular Data
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:14:57.273950Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 08693777-4843-42e2-a359-856740e6586d · inbound
TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks cites this paper.
TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks Large Language Models Engineer Too Many Simple Features For Tabular Data
Reference 64
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T22:06:16.795910Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.