Paper Citation Record · LEDGER

Auto-PINN: Understanding and Optimizing Physics-Informed Neural Architecture

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2205.13748.

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

pith.paper-citation-record.v1
2205.13748 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:38:24.719842Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T12:56:14.900613Z

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 8f761cbb-fc5a-479d-948b-5a6182895f86 · inbound

PINNsAgent: Automated PDE Surrogation with Large Language Models cites this paper.

PINNsAgent: Automated PDE Surrogation with Large Language Models Auto-PINN: Understanding and Optimizing Physics-Informed Neural Architecture

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T17:38:24.719842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fbf4031-fe8e-49c5-8b4b-f7e869f33e96 · inbound

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion cites this paper.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Auto-PINN: Understanding and Optimizing Physics-Informed Neural Architecture

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T21:21:40.962626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2132007a-38c0-4bb0-89fa-7ed95e9a6f62 · inbound

A Simple but Efficient Transformer-Based Physics-Informed Neural Network for Incompressible Navier--Stokes Equations cites this paper.

A Simple but Efficient Transformer-Based Physics-Informed Neural Network for Incompressible Navier--Stokes Equations Auto-PINN: Understanding and Optimizing Physics-Informed Neural Architecture

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-21T17:05:24.270171Z

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 e0287d7c-4c0c-4b63-b969-f0e0eff96efc · inbound

Physics-Audited Agentic Discovery in Scientific Machine Learning cites this paper.

Physics-Audited Agentic Discovery in Scientific Machine Learning Auto-PINN: Understanding and Optimizing Physics-Informed Neural Architecture

Reference 36

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T12:56:14.902611Z

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.