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Paper Citation Record · LEDGER

PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:2307.11833.

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

pith.paper-citation-record.v1
2307.11833 v3

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measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 23 of 23 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 23 of 23 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T21:54:20.893092Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T18:30:02.715063Z

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 300c6392-67f3-4480-97f3-89d813fcaff5 · inbound

Enhancing Neural Function Approximation: The XNet Outperforming KAN cites this paper.

Enhancing Neural Function Approximation: The XNet Outperforming KAN PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 2023

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no resolver link, observed 2026-08-09T21:54:20.893092Z

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Observation c05a34e5-cd89-4d88-a02f-21ebb888f9b7 · inbound

Complex Physics-Informed Neural Network cites this paper.

Complex Physics-Informed Neural Network PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 39

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no resolver link, observed 2026-08-08T21:06:33.477351Z

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source=pdf_text observed=2026-08-08T21:06:33.477351Z digest=sha256:fdb97a275cf12c086632c4bb18599c2eef454c8b2f4aa94cb48eee602b7031fe

Observation ba637434-e286-4877-a106-d15c77dd52d6 · inbound

Machine learning for modelling unstructured grid data in computational physics: a review cites this paper.

Machine learning for modelling unstructured grid data in computational physics: a review PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 291

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no resolver link, observed 2026-08-07T21:49:41.703034Z

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Observation 53c51dd3-5fd3-4605-b0f3-758f16778186 · inbound

Hierarchical-embedding autoencoder with a predictor (HEAP) as efficient architecture for learning long-term evolution of complex multi-scale physical systems cites this paper.

Hierarchical-embedding autoencoder with a predictor (HEAP) as efficient architecture for learning long-term evolution of complex multi-scale physical systems PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 85

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no resolver link, observed 2026-08-07T14:27:44.171921Z

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source=pdf_text observed=2026-08-07T14:27:44.171921Z digest=sha256:caec4b2718a9d5012b11d70e7e51189e68977871341acde78598c11c347b24a7

Observation 0f90cf8b-b2cf-44bf-8c28-70f1962c67a3 · inbound

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks cites this paper.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 90

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no resolver link, observed 2026-08-07T11:16:00.431695Z

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source=arxiv_source observed=2026-08-07T11:16:00.431695Z digest=sha256:67eb54b157df969fa37728266183d1cbac8eb83f89098b76b62cc8ac32705f78

Observation 789327a9-3f9b-456b-b837-a8f3a870c49b · inbound

Learning Mappings in Mesh-based Simulations cites this paper.

Learning Mappings in Mesh-based Simulations PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 42

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no resolver link, observed 2026-08-07T00:50:33.901607Z

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Observation c8cad124-138e-4246-a334-d9c8caf05e87 · inbound

Towards Digital Twins for Optimal Radioembolization cites this paper.

Towards Digital Twins for Optimal Radioembolization PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 64

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no resolver link, observed 2026-08-05T13:48:46.899564Z

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source=pdf_text observed=2026-08-05T13:48:46.899564Z digest=sha256:ba41fa20e0511d87a2ac4f146ec6042ac7eb2f2b58a6cf3df93c70f177f25dbb

Observation d2223b3e-6dd1-48d0-85b7-c5569fc65994 · inbound

Neural Multiscale Decomposition for Solving The Nonlinear Klein-Gordon Equation with Time Oscillation cites this paper.

Neural Multiscale Decomposition for Solving The Nonlinear Klein-Gordon Equation with Time Oscillation PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 2022

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no resolver link, observed 2026-08-03T19:36:17.508809Z

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Observation ecdea05b-c48b-4f08-a647-0b6184923c4a · inbound

Integrating Fourier Neural Operator with Diffusion Model for Autoregressive Predictions of Three-dimensional Turbulence cites this paper.

Integrating Fourier Neural Operator with Diffusion Model for Autoregressive Predictions of Three-dimensional Turbulence PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 82

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no resolver link, observed 2026-08-03T16:37:40.545502Z

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Observation e7c69c31-27c2-485e-8ab0-bc4676d01c00 · 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 PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 22

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verified exact
arxiv_id, observed 2026-05-21T17:05:24.294087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation c6c4940b-df26-4ac1-83b9-3b06637ff493 · inbound

When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions cites this paper.

When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 30

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metadata mismatch
arxiv_id, observed 2026-05-11T21:06:14.680626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 0a5f7b86-25a9-4b9b-92d2-04492db7692f · inbound

Can Transformers predict system collapse in dynamical systems? cites this paper.

Can Transformers predict system collapse in dynamical systems? PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 51

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verified exact
arxiv_id, observed 2026-05-12T10:41:31.553857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 4651642f-32cf-420b-b917-f130d60b854c · inbound

Deep Wave Network for Modeling Multi-Scale Physical Dynamics cites this paper.

Deep Wave Network for Modeling Multi-Scale Physical Dynamics PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 27

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arxiv_id, observed 2026-05-11T17:31:04.852599Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 13543649-cb1d-47b1-bdf9-0d1c88e92d39 · inbound

Physics-Informed Neural Networks with Attention Feature Expansion for Monge-Amp\`ere Equations cites this paper.

Physics-Informed Neural Networks with Attention Feature Expansion for Monge-Amp\`ere Equations PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 50

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verified exact
arxiv_id, observed 2026-05-22T04:16:02.619108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 6a485b04-cb40-43b9-9b82-fbf4696c4da2 · inbound

Multi-Scale Separable Fourier Neural Networks for Solving High-Frequency PDEs cites this paper.

Multi-Scale Separable Fourier Neural Networks for Solving High-Frequency PDEs PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 26

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arxiv_id, observed 2026-06-29T00:02:49.782873Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation d2f10747-8bfc-47c7-a70b-c9e4c2c64c30 · inbound

Curvature-aware dynamic precision approach for physics-informed neural networks cites this paper.

Curvature-aware dynamic precision approach for physics-informed neural networks PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 53

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arxiv_id, observed 2026-07-02T06:06:41.648172Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 07ac87ac-9016-42bf-967d-60eeb586c8da · inbound

Physics-Informed Neural Network with Squeeze-Excitation-like Attention cites this paper.

Physics-Informed Neural Network with Squeeze-Excitation-like Attention PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 39

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verified exact
arxiv_id, observed 2026-07-04T03:29:30.203869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 66bac173-c9f1-4b88-8807-88b287ccfc88 · inbound

A Physics-Informed Fourier-Wavelet Transformer for Multiscale Computational Fluid Dynamics Surrogate Modeling cites this paper.

A Physics-Informed Fourier-Wavelet Transformer for Multiscale Computational Fluid Dynamics Surrogate Modeling PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 17

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verified exact
arxiv_id, observed 2026-07-04T18:30:02.716937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 8d3f8a16-7a84-4c26-a169-2e6a07d7a487 · inbound

LLT: Local Linear Transformer for PDE Operator Learning cites this paper.

LLT: Local Linear Transformer for PDE Operator Learning PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 35

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Observation c4980f34-7c04-43d2-825f-e33f7012b1fd · inbound

A new strategy for physics-informed neural networks based on hierarchical collocation point refinement cites this paper.

A new strategy for physics-informed neural networks based on hierarchical collocation point refinement PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 6

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Observation 6183cf8b-4dc3-4209-8b53-ee911760b0db · inbound

Harnessing Machine Learning for Hybrid Constitutive Modelling of Viscoelastic Fluid Flows in Computational Rheology cites this paper.

Harnessing Machine Learning for Hybrid Constitutive Modelling of Viscoelastic Fluid Flows in Computational Rheology PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 28

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Observation d1eca3f9-bc46-4c95-b7f4-54355f4b9135 · inbound

Split Complex-Valued Physics-Informed Neural Networks for Forward and Inverse Nonlinear PDEs cites this paper.

Split Complex-Valued Physics-Informed Neural Networks for Forward and Inverse Nonlinear PDEs PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 59

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no resolver link, observed 2026-08-02T00:14:59.506851Z

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Observation 531f38f6-04de-475c-bb3f-21c51d12b9ee · inbound

Cosmo-SPINN: Fuzzy Dark Matter Simulations with Physics-Informed Generative Networks cites this paper.

Cosmo-SPINN: Fuzzy Dark Matter Simulations with Physics-Informed Generative Networks PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 64

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no resolver link, observed 2026-07-31T02:27:16.981188Z

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