Paper Citation Record · LEDGER

Multi-Grid Graph Neural Networks with Self-Attention for Computational Mechanics

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2409.11899.

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

pith.paper-citation-record.v1
2409.11899 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:24:33.451875Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T21:35:04.198280Z

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 ed346ba9-8d9a-44d6-97eb-ac44d1e997dc · inbound

MeshMask: Physics-Based Simulations with Masked Graph Neural Networks cites this paper.

MeshMask: Physics-Based Simulations with Masked Graph Neural Networks Multi-Grid Graph Neural Networks with Self-Attention for Computational Mechanics

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:33.446608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b49edd38-3163-4232-b87e-f2480b0c1a32 · inbound

MeshMask: Physics-Based Simulations with Masked Graph Neural Networks cites this paper.

MeshMask: Physics-Based Simulations with Masked Graph Neural Networks Multi-Grid Graph Neural Networks with Self-Attention for Computational Mechanics

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:33.451875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88358106-9faa-48c3-81cd-322a95f3a1d6 · inbound

Automated discovery of finite volume schemes using Graph Neural Networks cites this paper.

Automated discovery of finite volume schemes using Graph Neural Networks Multi-Grid Graph Neural Networks with Self-Attention for Computational Mechanics

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:43.820476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1612aa65-b278-4fdc-87e6-62e55f049980 · inbound

Mask-Morph Graph U-Net: A Generalisable Mesh-Based Surrogate for Crashworthiness Field Prediction under Large Geometric Variation cites this paper.

Mask-Morph Graph U-Net: A Generalisable Mesh-Based Surrogate for Crashworthiness Field Prediction under Large Geometric Variation Multi-Grid Graph Neural Networks with Self-Attention for Computational Mechanics

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:42:39.814845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9308ee51-9962-4809-a5fa-381f05dc8913 · inbound

Mask-Morph Graph U-Net: A Generalisable Mesh-Based Surrogate for Crashworthiness Field Prediction under Large Geometric Variation cites this paper.

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:35:04.199553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0ae35d6f-c689-42f3-909a-48df487f202c · inbound

Physics-Informed Coarsening for Multigrid Graph Neural Surrogates cites this paper.

Physics-Informed Coarsening for Multigrid Graph Neural Surrogates Multi-Grid Graph Neural Networks with Self-Attention for Computational Mechanics

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T00:02:50.427421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.