Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
OccamNet: A Fast Neural Model for Symbolic Regression at Scale
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2007.10784.
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 2026-08-05T14:20:39.468217Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T23:42:04.165141Z
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 b0194158-60e9-4d39-ba0c-f5eeeb3e9450 · inbound
KAN: Kolmogorov-Arnold Networks cites this paper.
KAN: Kolmogorov-Arnold Networks OccamNet: A Fast Neural Model for Symbolic Regression at Scale
Reference 98
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T23:42:04.216955Z
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.
Observation 4b2c0689-efc7-4457-8147-14c0d79cfe89 · inbound
Data-driven Discovery of Digital Twins in Biomedical Research cites this paper.
Data-driven Discovery of Digital Twins in Biomedical Research OccamNet: A Fast Neural Model for Symbolic Regression at Scale
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:20:39.468217Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fd761975-56a0-4e33-a464-986739f4fc35 · inbound
Singularity Formation: Synergy in Theoretical, Numerical and Machine Learning Approaches cites this paper.
Singularity Formation: Synergy in Theoretical, Numerical and Machine Learning Approaches OccamNet: A Fast Neural Model for Symbolic Regression at Scale
Reference 98
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T09:23:37.390762Z
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.