Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
GoRINNs: Godunov-Riemann Informed Neural Networks for Learning Hyperbolic Conservation Laws
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.22193.
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 2026-08-07T14:28:25.622776Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T14:28:29.875418Z
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 ca9bde07-3592-4216-be9e-e8e79770a7ac · inbound
A "Neural" Riemann solver for Relativistic Hydrodynamics cites this paper.
A "Neural" Riemann solver for Relativistic Hydrodynamics GoRINNs: Godunov-Riemann Informed Neural Networks for Learning Hyperbolic Conservation Laws
Reference 24
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T14:28:29.966043Z
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.
Observation 5adb435a-89e0-41ca-8cca-9a2d83dd0cda · inbound
HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws cites this paper.
HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws GoRINNs: Godunov-Riemann Informed Neural Networks for Learning Hyperbolic Conservation Laws
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T07:31:24.450338Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.