Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Equivariant Matrix Function Neural Networks
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2310.10434.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T14:00:16.843897Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T19:37:19.115296Z
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 71bea8b5-bc6c-422f-88f0-4b230bc47e09 · inbound
Fast automatically differentiable matrix functions and applications in molecular simulations cites this paper.
Fast automatically differentiable matrix functions and applications in molecular simulations Equivariant Matrix Function Neural Networks
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T14:00:16.843897Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 19859d4d-d87b-44c8-82ab-e3449130c212 · inbound
Learning the Electronic Hamiltonian of Large Atomic Structures cites this paper.
Learning the Electronic Hamiltonian of Large Atomic Structures Equivariant Matrix Function Neural Networks
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T21:26:28.203901Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 45402d9c-455a-4059-9301-c1ab0728d22c · inbound
Six Open Questions in Machine-Learned Interatomic Potential Foundation Models cites this paper.
Six Open Questions in Machine-Learned Interatomic Potential Foundation Models Equivariant Matrix Function Neural Networks
Reference 98
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T19:37:19.116541Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.