Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Prove Symbolic Regression is NP-hard by Symbol Graph
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2404.13820.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-14T20:50:12.237932Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-14T20:52:58.896444Z
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 fe202296-6d6e-4e13-93a7-8418a4f244c8 · inbound
FePySR: A Neural Feature Extraction Framework for Efficient and Scalable Symbolic Regression cites this paper.
FePySR: A Neural Feature Extraction Framework for Efficient and Scalable Symbolic Regression Prove Symbolic Regression is NP-hard by Symbol Graph
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T20:52:58.899429Z
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.