Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Continuous-mixture Autoregressive Networks for efficient variational calculation of many-body systems
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2005.04857.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T13:19:35.125667Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-09T13:19:35.541433Z
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 6b9bdedb-1391-4e0b-a903-87c3473bf082 · inbound
Exploring Generative Networks for Manifolds with Non-Trivial Topology cites this paper.
Exploring Generative Networks for Manifolds with Non-Trivial Topology Continuous-mixture Autoregressive Networks for efficient variational calculation of many-body systems
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-08-09T13:19:35.546894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 3c5e00cc-7fe1-4f10-8de5-eca4b8179ee8 · inbound
Symmetry-preserving neural networks in lattice field theories cites this paper.
Symmetry-preserving neural networks in lattice field theories Continuous-mixture Autoregressive Networks for efficient variational calculation of many-body systems
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:58:31.910974Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 521b6cf3-e711-49f8-9849-dcf992b24683 · inbound
Heavy Quarkonium Spectrum and Decay Constants from a Neural-Network-Based Holographic Model cites this paper.
Heavy Quarkonium Spectrum and Decay Constants from a Neural-Network-Based Holographic Model Continuous-mixture Autoregressive Networks for efficient variational calculation of many-body systems
Reference 64
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T08:12:16.564751Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.