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Paper Citation Record · LEDGER

When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2109.09444.

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

pith.paper-citation-record.v1
2109.09444 v7

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:23:40.808707Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:19:44.067889Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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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 9d2d7488-a6d5-4ca9-961b-5f5fcf2e2c61 · inbound

Physics-informed solution reconstruction in elasticity and heat transfer using the explicit constraint force method cites this paper.

Physics-informed solution reconstruction in elasticity and heat transfer using the explicit constraint force method When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-15T23:23:40.808707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:23:40.808707Z digest=sha256:8e0cddb299c8f2913e46531d2e71ecc705c3b9e30b50da26c7ee6d07428de5b2

Observation 953491f8-dd0b-4a46-8735-2d9eea4d6f1b · inbound

BridgeNet: A Hybrid, Physics-Informed Machine Learning Framework for Solving High-Dimensional Fokker-Planck Equations cites this paper.

BridgeNet: A Hybrid, Physics-Informed Machine Learning Framework for Solving High-Dimensional Fokker-Planck Equations When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T10:50:50.503897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:50:50.503897Z digest=sha256:a0faf62de9d8edc1912dd86ce46dea38a38bf78f1529919e471c1b9ae3b3b7c2

Observation 93922a95-dd0a-4e75-958f-81600e770a85 · inbound

ViscoReg: Neural Signed Distance Functions via Viscosity Solutions cites this paper.

ViscoReg: Neural Signed Distance Functions via Viscosity Solutions When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-06T21:27:41.824209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:27:41.824209Z digest=sha256:33f85c8729e245ee4c1fc46417c8148e80cd4e91679181205adc059accbec10d

Observation 5c20c0e9-93e7-4aea-9c38-2a4042e8adf5 · inbound

Estimating Parameter Fields in Multi-Physics PDEs from Scarce Measurements cites this paper.

Estimating Parameter Fields in Multi-Physics PDEs from Scarce Measurements When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:22:49.261856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T19:17:13.031769Z digest=sha256:e11a93d8c109c17e4c2d63ff4bd51a9345c90f6dc12d50cc1dd864e3b532c89c

Observation 0d503e32-d467-4c23-a191-81c6e066b1b9 · inbound

Faster by Design: Interactive Aerodynamics via Neural Surrogates Trained on Expert-Validated CFD cites this paper.

Faster by Design: Interactive Aerodynamics via Neural Surrogates Trained on Expert-Validated CFD When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?

Reference 23

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T06:11:20.672323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-10T05:42:41.806371Z digest=sha256:7f48f88f5b882b00417b97ae0cc083cec9dd394b47a13b954b8d6fceb8627a06

Observation db21300a-6b92-466b-aec0-79eac41c89ab · inbound

Adaptive Domain Decomposition Physics-Informed Neural Networks for Traffic State Estimation with Sparse Sensor Data cites this paper.

Adaptive Domain Decomposition Physics-Informed Neural Networks for Traffic State Estimation with Sparse Sensor Data When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:10:53.452591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-11T02:37:54.633059Z digest=sha256:9fcfd89364c3802d3509d42248f615bcb2fba40df1e374fac20ef17b079f562f

Observation b1d6ac3d-aaf3-49a7-8a88-3126c9223e13 · inbound

Beyond Data-Driven: How Physics-Informed Neural Networks are Reshaping Multi-Physics Design and Discovery cites this paper.

Beyond Data-Driven: How Physics-Informed Neural Networks are Reshaping Multi-Physics Design and Discovery When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?

Reference 50

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T08:19:44.069478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-26T11:55:25.831089Z digest=sha256:ebf78358b4354b922dc0424ad63a23b6ed4f44c97a97c3755eaa229eac42e51a