Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Neural-Network-Based Selective Configuration Interaction Approach to Molecular Electronic Structure
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.08154.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T15:33:58.190187Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T14:39:58.308474Z
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 aebb9fa4-ed48-4205-beb8-2459a5ce559d · inbound
An Iterative Dual-Channel Neural Quantum State Algorithm for Selected Configuration Interaction cites this paper.
An Iterative Dual-Channel Neural Quantum State Algorithm for Selected Configuration Interaction A Neural-Network-Based Selective Configuration Interaction Approach to Molecular Electronic Structure
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T14:39:58.310451Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 20ff22d9-7bfb-4ca5-95a6-8a40124b90cb · 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 A Neural-Network-Based Selective Configuration Interaction Approach to Molecular Electronic Structure
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T15:33:58.190187Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.