Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Learning in PINNs: Phase transition, total diffusion, and generalization
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2403.18494.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T13:58:34.090259Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
11
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 55a95b99-d1a3-4d23-8d82-630443939f0f · inbound
Multi-Resolution Training-Enhanced Kolmogorov-Arnold Networks for Multi-Scale PDE Problems cites this paper.
Multi-Resolution Training-Enhanced Kolmogorov-Arnold Networks for Multi-Scale PDE Problems Learning in PINNs: Phase transition, total diffusion, and generalization
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:58:34.090259Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 39b13096-8085-4390-9ae2-1c8e166b5f33 · inbound
Estimating bottom topography in shallow water flows cites this paper.
Estimating bottom topography in shallow water flows Learning in PINNs: Phase transition, total diffusion, and generalization
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T18:15:42.508506Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 76608982-fc12-461e-b2aa-0a6826dd04b1 · inbound
Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence cites this paper.
Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Learning in PINNs: Phase transition, total diffusion, and generalization
Reference 74
- Resolution
- verified exact
- local_arxiv, observed 2026-07-09T21:46:34.600002Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.