Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Finite Volume Graph Network(FVGN): Predicting unsteady incompressible fluid dynamics with finite volume informed neural network
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2309.10050.
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 2026-08-06T15:12:03.530488Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T19:25:01.127177Z
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 0dcee799-4275-423b-9a09-21758175b230 · inbound
Data-Driven Adaptive Gradient Recovery for Unstructured Finite Volume Computations cites this paper.
Data-Driven Adaptive Gradient Recovery for Unstructured Finite Volume Computations Finite Volume Graph Network(FVGN): Predicting unsteady incompressible fluid dynamics with finite volume informed neural network
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:12:03.530488Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d11661d4-f506-4d85-80b3-c3143d337dc0 · inbound
Bridging Data and Physics: A Graph Neural Network-Based Hybrid Twin Framework cites this paper.
Bridging Data and Physics: A Graph Neural Network-Based Hybrid Twin Framework Finite Volume Graph Network(FVGN): Predicting unsteady incompressible fluid dynamics with finite volume informed neural network
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T07:30:28.018383Z
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 61bb667c-e61c-44ee-9411-fa67f3d31e5c · inbound
A finite-element-inspired bipartite graph learned simulator for manufacturability assessment in large-deformation sheet forming cites this paper.
A finite-element-inspired bipartite graph learned simulator for manufacturability assessment in large-deformation sheet forming Finite Volume Graph Network(FVGN): Predicting unsteady incompressible fluid dynamics with finite volume informed neural network
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T00:36:30.014805Z
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 b65bd013-b48c-4dc5-b516-c8ece30d540b · inbound
A finite-element-inspired bipartite graph learned simulator for manufacturability assessment in large-deformation sheet forming cites this paper.
A finite-element-inspired bipartite graph learned simulator for manufacturability assessment in large-deformation sheet forming Finite Volume Graph Network(FVGN): Predicting unsteady incompressible fluid dynamics with finite volume informed neural network
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T19:25:01.128521Z
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.