Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Ab-initio quantum chemistry with neural-network wavefunctions
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2208.12590.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T15:33:58.278896Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
11
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 120e2a60-d86e-4c20-85b6-917f4270981a · inbound
Approximating Hartree-Fock theory via an efficiently local reformulation cites this paper.
Approximating Hartree-Fock theory via an efficiently local reformulation Ab-initio quantum chemistry with neural-network wavefunctions
Reference 129
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T12:02:06.416190Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation daf48192-b354-4496-9759-1c4ecc206df3 · inbound
Medium-mass nuclei with neural quantum states cites this paper.
Medium-mass nuclei with neural quantum states Ab-initio quantum chemistry with neural-network wavefunctions
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T04:35:37.457654Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b36198a-be55-41b0-b772-d2bb14513464 · inbound
Machine learning for sample-based quantum diagonalization: generative configuration recovery and the classical-simulability frontier cites this paper.
Machine learning for sample-based quantum diagonalization: generative configuration recovery and the classical-simulability frontier Ab-initio quantum chemistry with neural-network wavefunctions
Reference 80
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T15:33:58.278896Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.