Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
On the Trainability and Classical Simulability of Learning Matrix Product States Variationally
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2409.10055.
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 2026-08-11T05:32:14.012720Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T05:32:14.128727Z
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 755aea22-9018-4645-9b81-138a9f13ac3c · inbound
Advantages of density in tensor network geometries for gradient based training cites this paper.
Advantages of density in tensor network geometries for gradient based training On the Trainability and Classical Simulability of Learning Matrix Product States Variationally
Reference 50
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T05:32:14.136322Z
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.