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Paper Citation Record · LEDGER

Neural Operators for Accelerating Scientific Simulations and Design

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2309.15325.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2309.15325 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:51:20.129523Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T20:35:15.944343Z

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 69b391a1-4646-4e13-b9c2-e66c0c843cc8 · inbound

Computational Math with Neural Networks is Hard cites this paper.

Computational Math with Neural Networks is Hard Neural Operators for Accelerating Scientific Simulations and Design

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T14:51:20.129523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:51:20.129523Z digest=sha256:169dcec54bee4465be5bf90b39bd92653628fc06992c2629c00b199d8019812d

Observation ac8784bf-eb9d-4904-b3d6-e7be35e89c2a · inbound

Solving engineering eigenvalue problems with neural networks using the Rayleigh quotient cites this paper.

Solving engineering eigenvalue problems with neural networks using the Rayleigh quotient Neural Operators for Accelerating Scientific Simulations and Design

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T10:48:10.360908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:48:10.360908Z digest=sha256:b18137d5b1bffc8806b0b0952399acbd2bee9f1e1c29cd3fa390235ee94b735a

Observation b967fc93-8f5f-4c09-8902-117e75dda3bd · inbound

Toward a Robust and Generalizable Metamaterial Foundation Model cites this paper.

Toward a Robust and Generalizable Metamaterial Foundation Model Neural Operators for Accelerating Scientific Simulations and Design

Reference 32

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:35:16.076933Z

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.

source=pdf_text observed=2026-08-06T20:35:14.445044Z digest=sha256:4d4619fd8995a4f92c1a4e73511adbd07bf940b524856babd57bbda2f778c47b