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Paper Citation Record · LEDGER

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition

As of 8 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2507.08861.

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

pith.paper-citation-record.v1
2507.08861 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:02:45.519867Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

47 of 47 outbound references displayed

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External citation measurements

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Outbound references

Observation 20208dd6-45a2-47cf-ba64-9ebe7e1d0d40 · outbound

This paper cites Machine learning in computer aided engineering.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Machine learning in computer aided engineering

Reference 1

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This paper cites Learning mesh-based simulation with graph networks.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Learning mesh-based simulation with graph networks

Reference 2

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This paper cites Physics-based machine learning for computational fracture mechanics.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Physics-based machine learning for computational fracture mechanics

Reference 3

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Observation 4209e14a-03e5-4f53-acf0-5318873fa08a · outbound

This paper cites Flowgnn: A dataflow architecture for real-time workload-agnostic graph neural network inference.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Flowgnn: A dataflow architecture for real-time workload-agnostic graph neural network inference

Reference 4

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Observation 82fee802-7195-469a-88ba-d89307558f52 · outbound

This paper cites Zahr, and Jian-Xun Wang.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Zahr, and Jian-Xun Wang

Reference 5

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Observation 78eb4bde-8176-4355-9e7b-a27eeaab317f · outbound

This paper cites GraphCast: Learning skillful medium-range global weather forecasting.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition GraphCast: Learning skillful medium-range global weather forecasting

Reference 6

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Observation e726e8ed-0c8f-4ec5-b420-3d741bddd07a · outbound

This paper cites Calculus of Finite Differences, volume 33.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Calculus of Finite Differences, volume 33

Reference 7

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Observation eec50e71-c327-40ea-9539-3b4bf919ac29 · outbound

This paper cites Finite element method.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Finite element method

Reference 8

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Observation a2faa05f-ccbf-461c-a419-ec4bbaf6ee63 · outbound

This paper cites Finite volume methods.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Finite volume methods

Reference 9

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Observation 2cfd0ad0-34ef-4b0b-9ae4-507bf721403c · outbound

This paper cites Kevrekidis, Lu Lu, Paris Perdikaris, Sifan Wang, and Liu Yang.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Kevrekidis, Lu Lu, Paris Perdikaris, Sifan Wang, and Liu Yang

Reference 10

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Observation fd194a66-41f4-494d-96ce-fa9208d39c09 · outbound

This paper cites A review of graph neural network applications in mechanics-related domains.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition A review of graph neural network applications in mechanics-related domains

Reference 11

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Observation 438e78ce-1a59-47a3-a4bc-48e48e3aca61 · outbound

This paper cites Allen, Tatiana Lopez-Guevara, Kimberly Stachenfeld, Alvaro Sanchez-Gonzalez, Peter Battaglia, Jessica Hamrick, and Tobias Pfaff.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Allen, Tatiana Lopez-Guevara, Kimberly Stachenfeld, Alvaro Sanchez-Gonzalez, Peter Battaglia, Jessica Hamrick, and Tobias Pfaff

Reference 12

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This paper cites Allen, Yulia Rubanova, Tatiana Lopez-Guevara, William Whitney, Alvaro Sanchez-Gonzalez, Peter Battaglia, and Tobias Pfaff.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Allen, Yulia Rubanova, Tatiana Lopez-Guevara, William Whitney, Alvaro Sanchez-Gonzalez, Peter Battaglia, and Tobias Pfaff

Reference 13

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This paper cites Iparraguirre, Icíar Alfaro, David González, Francisco Chinesta, and Elías Cueto.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Iparraguirre, Icíar Alfaro, David González, Francisco Chinesta, and Elías Cueto

Reference 14

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Observation f8a83c25-97de-45d8-af11-909f9b1a75cc · outbound

This paper cites Scientific machine learning through physics–informed neural networks: Where we are and what’s next.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Scientific machine learning through physics–informed neural networks: Where we are and what’s next

Reference 15

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Source-reported events for the cited work

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This paper cites Physics-informed neural networks (pinns) for fluid mechanics: a review.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Physics-informed neural networks (pinns) for fluid mechanics: a review

Reference 16

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Observation 362ad761-7d8d-43cd-993e-5d9cc3c9f863 · outbound

This paper cites Dpm: A novel training method for physics-informed neural networks in extrapolation.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Dpm: A novel training method for physics-informed neural networks in extrapolation

Reference 17

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This paper cites Understanding and mitigating extrapolation failures in physics-informed neural networks, 2023.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Understanding and mitigating extrapolation failures in physics-informed neural networks, 2023

Reference 18

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This paper cites A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized pdes.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized pdes

Reference 19

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Observation 2eef5cef-1f45-4837-865c-fa7c1f05c86a · outbound

This paper cites Pod-dl-rom: Enhancing deep learning-based reduced order models for nonlinear parametrized pdes by proper orthogonal decomposition.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Pod-dl-rom: Enhancing deep learning-based reduced order models for nonlinear parametrized pdes by proper orthogonal decomposition

Reference 20

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This paper cites Handling geometrical variability in nonlinear reduced order modeling through continuous geometry-aware dl-roms.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Handling geometrical variability in nonlinear reduced order modeling through continuous geometry-aware dl-roms

Reference 21

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This paper cites Gradient-based learning applied to document recognition.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Gradient-based learning applied to document recognition

Reference 22

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This paper cites Bronstein, Joan Bruna, Taco Cohen, and Petar Veliˇckovi´c.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Bronstein, Joan Bruna, Taco Cohen, and Petar Veliˇckovi´c

Reference 23

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This paper cites Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, and Pierre Vandergheynst.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, and Pierre Vandergheynst

Reference 24

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On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Unresolved cited work

Reference 25

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This paper cites Unravelling the performance of physics-informed graph neural networks for dynamical systems.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Unravelling the performance of physics-informed graph neural networks for dynamical systems

Reference 26

Resolution
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On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Unresolved cited work

Reference 27

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On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Thermodynamics-informed graph neural networks

Reference 28

Resolution
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On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Structure-preserving neural networks

Reference 29

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This paper cites Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems

Reference 30

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Observation 77907e2d-1c98-4dbb-a2b8-5428c13f5a0c · outbound

This paper cites Thermodynamics-informed neural networks for physically realistic mixed reality.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Thermodynamics-informed neural networks for physically realistic mixed reality

Reference 31

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Source-reported events for the cited work

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Observation 89085e35-6b5c-4e5c-ac50-e61792d768bd · outbound

This paper cites Graph neural networks informed locally by thermodynamics.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Graph neural networks informed locally by thermodynamics

Reference 32

Resolution
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Source-reported events for the cited work

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Observation ab1103c6-1f0f-4abc-a3ba-f25a5d4e20b2 · outbound

This paper cites Reversible and irreversible bracket-based dynamics for deep graph neural networks.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Reversible and irreversible bracket-based dynamics for deep graph neural networks

Reference 33

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raw_fallback, observed 2026-08-06T19:02:45.858478Z

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=2026-08-06T19:02:45.447849Z digest=sha256:546f49c1a47da545a40fe6e2ebc64fc38d1ffd45a9320c82583d16ab2ff73f9e

Observation 60331e5e-9431-482d-8a2d-a4faebf6a956 · outbound

This paper cites A thermodynamics-informed active learning approach to perception and reasoning about fluids.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition A thermodynamics-informed active learning approach to perception and reasoning about fluids

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:02:45.842576Z

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=2026-08-06T19:02:45.453043Z digest=sha256:bb3483b1f32346f4190fa2ee60ace53b6d77f3e78170fd403f9e55693a54ca9f

Observation 38dcdffc-989a-4187-99d0-e478e65f1dce · outbound

This paper cites Thermodynamics- informed super-resolution of scarce temporal dynamics data.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Thermodynamics- informed super-resolution of scarce temporal dynamics data

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:02:45.825616Z

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=2026-08-06T19:02:45.457921Z digest=sha256:880ec309f93a51ebb0edb201952c6fde7818b3e83bb738ffab6225bb9de3fb67

Observation 43bc686c-f200-4855-b40d-4cd1310470c3 · outbound

This paper cites Hyperparameter Optimization, pages 3–33.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Hyperparameter Optimization, pages 3–33

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:02:45.805792Z

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=2026-08-06T19:02:45.462616Z digest=sha256:a0f085a032d2e657b0ac7afd18265967a7e0d61bf87aedbe5242a12e89f7028c

Observation 75e609a2-b110-4067-9219-2542a2afd49f · outbound

This paper cites Breaking the limits of message passing graph neural networks.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Breaking the limits of message passing graph neural networks

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:02:45.784393Z

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=2026-08-06T19:02:45.467234Z digest=sha256:3dad0fb123b8a06f02a3c03acef82d3ddcb5e62c884eb796beb296c4bb56012e

Observation 5dcc2ac0-0f8d-4598-980b-5f3c1799bb73 · outbound

This paper cites an unresolved cited work.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-06T19:02:45.768136Z

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=2026-08-06T19:02:45.471980Z digest=sha256:9bbd928636248a9b139f1b4978d6d5117931e52f26f7337416283a90842eb380

Observation bd6e5055-1b9f-4ec6-b8e7-f4f6bb722eba · outbound

This paper cites The paradox of fourier heat equation: A theoretical refutation.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition The paradox of fourier heat equation: A theoretical refutation

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:02:45.750491Z

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=2026-08-06T19:02:45.477021Z digest=sha256:8732273f7bf5ebc801916cad81b24e24ee84f0b095f89c7a40c91c6aa11c398a

Observation e22712ef-7e75-4a1e-b843-26b6d1a25275 · outbound

This paper cites Schoenholz, Patrick F.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Schoenholz, Patrick F

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:02:45.733500Z

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=2026-08-06T19:02:45.482872Z digest=sha256:cfc7a70f4d58e44ba668d25eec65354b815c7d6361b5ac5243a84296fd4e68ba

Observation 70c7f087-08cc-4732-b08d-4045854b39ca · outbound

This paper cites Nodemixup: Tackling under-reaching for graph neural networks.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Nodemixup: Tackling under-reaching for graph neural networks

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:02:45.716233Z

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=2026-08-06T19:02:45.487806Z digest=sha256:e0b597f25bfe1503566bac78aaef4f6b84a13859f6b45041edf4982a83b6422c

Observation ff3291ff-16c9-421c-b270-f45e6b84b5a2 · outbound

This paper cites Message Passing Neural PDE Solvers.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Message Passing Neural PDE Solvers

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T19:02:45.492304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:02:45.492304Z digest=sha256:575af878b7e6eb3422fa4c49408c0a5a851650551e2fe288034c488ac05fc945

Observation b0869365-2251-444b-bf07-cdd802ac1589 · outbound

This paper cites The Courant–Friedrichs–Lewy (CFL) condition.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition The Courant–Friedrichs–Lewy (CFL) condition

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:02:45.699967Z

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=2026-08-06T19:02:45.496906Z digest=sha256:2b70ece1453c340bb30c95ba323d2e78ba329cfdffc4c3ea30480241a48a33c3

Observation 0f87a8c6-347a-46b0-ad3f-f8fdb4243126 · outbound

This paper cites On the speed of heat.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition On the speed of heat

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:02:45.683590Z

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=2026-08-06T19:02:45.501618Z digest=sha256:b45d49494b9cfb0a1ba0b3cac05896c983d0773634832f884253b7e63439a8de

Observation 09cff1e6-5f34-48c8-aeee-201788131bbb · outbound

This paper cites Understanding over-squashing and bottlenecks on graphs via curvature.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Understanding over-squashing and bottlenecks on graphs via curvature

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:02:45.665785Z

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=2026-08-06T19:02:45.507097Z digest=sha256:cba53a22248a36604770fb633c00bb84e00697a0056109c15e04b2a4591cc479

Observation 389c18af-1fc2-4ce1-bdd1-106369218f55 · outbound

This paper cites Limits of depth: Over-smoothing and over-squashing in gnns.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Limits of depth: Over-smoothing and over-squashing in gnns

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:02:45.649005Z

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=2026-08-06T19:02:45.513916Z digest=sha256:e04d03b2556549f6172c5e251c81fb5ee47a748b0a6cb671c4b0b703b2a46c92

Observation ff59d60e-7f09-4e13-a05b-76dc4856114f · outbound

This paper cites Limiting Over-Smoothing and Over-Squashing of Graph Message Passing by Deep Scattering Transforms.

On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition Limiting Over-Smoothing and Over-Squashing of Graph Message Passing by Deep Scattering Transforms

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-08-06T19:02:45.588244Z

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=2026-08-06T19:02:45.519867Z digest=sha256:3b89a2093bd12a5027132dbb08513474f92094f0c5dd0aaca40112de35e77ff7

Pith citing papers

No inbound Pith citation observations are available.