Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Regressive and generative neural networks for scalar field theory
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1810.12879.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T11:38:41.354041Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-05-19T22:27:49.548899Z
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 538f2bdb-c26e-44a8-9338-a90bd029e8fd · inbound
Machine-learning approaches to accelerating lattice simulations cites this paper.
Machine-learning approaches to accelerating lattice simulations Regressive and generative neural networks for scalar field theory
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T11:38:41.354041Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0cabe103-4889-4c11-ba78-6b9bbcc28047 · inbound
Symmetry-preserving neural networks in lattice field theories cites this paper.
Symmetry-preserving neural networks in lattice field theories Regressive and generative neural networks for scalar field theory
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:58:31.820940Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c14e52e4-8d69-45ac-aa02-6ba5b48e2024 · inbound
Study of jet-induced hydro response in high-energy heavy-ion collisions with a flow-matching generative model cites this paper.
Study of jet-induced hydro response in high-energy heavy-ion collisions with a flow-matching generative model Regressive and generative neural networks for scalar field theory
Reference 88
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T22:27:49.550295Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.