Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Transformers as Neural Operators for Solutions of Differential Equations with Finite Regularity
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2405.19166.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T21:08:50.198621Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T22:48:32.859250Z
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 614e070c-a0af-4303-94b2-8aebeac027a1 · inbound
A DeepONet for inverting the Neumann-to-Dirichlet Operator in Electrical Impedance Tomography: An approximation theoretic perspective and numerical results cites this paper.
A DeepONet for inverting the Neumann-to-Dirichlet Operator in Electrical Impedance Tomography: An approximation theoretic perspective and numerical results Transformers as Neural Operators for Solutions of Differential Equations with Finite Regularity
Reference 76
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T22:48:32.863974Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 47c7694f-39dc-46a5-a7d5-506cc55d8dcc · inbound
Universal Approximation of Operators with Transformers and Neural Integral Operators cites this paper.
Universal Approximation of Operators with Transformers and Neural Integral Operators Transformers as Neural Operators for Solutions of Differential Equations with Finite Regularity
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T20:53:26.470885Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ea9ace80-a7ba-4820-b027-eb9f3804d807 · inbound
Crack Path Prediction with Operator Learning using Discrete Particle System data Generation cites this paper.
Crack Path Prediction with Operator Learning using Discrete Particle System data Generation Transformers as Neural Operators for Solutions of Differential Equations with Finite Regularity
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:08:50.198621Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.