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Paper Citation Record · LEDGER

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention

As of 19 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2605.27758.

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

pith.paper-citation-record.v1
2605.27758 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T18:06:55.696400Z

measured 42 of 42 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T09:18:45.158235Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

  • verified exact10
  • verified fuzzy0
  • unresolved31
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 98c28cec-a604-41e0-9f14-ac2acc652fca · outbound

This paper cites GeoTransolver: Learning Physics on Irregular Domains Using Multi-scale Geometry Aware Physics Attention Transformer.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention GeoTransolver: Learning Physics on Irregular Domains Using Multi-scale Geometry Aware Physics Attention Transformer

Reference 1

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local_arxiv, observed 2026-06-29T18:13:48.945061Z

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Observation 3d1c879a-326f-480c-b241-df8ee55240e9 · outbound

This paper cites Du Bois, C.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Du Bois, C

Reference 2

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Observation 9e12be74-acd1-4e5b-b8d5-00a2d1a1c6aa · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 3

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Observation f33723c9-df8d-4020-9e25-6e64a680fb00 · outbound

This paper cites Ozcan, S.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Ozcan, S

Reference 4

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source=pdf_text observed=2026-06-29T18:06:55.696400Z digest=sha256:b4bd8e86f3fe06311c68e5e9c7be0a95bfc7e176c657ebe3386ef9ab76bc946c

Observation 0d27ff2b-2535-48d3-a146-4ff74a93e2a0 · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 5

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Observation 98c25a1d-e922-4706-920d-5fd9ea6d8d24 · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 6

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Observation 57f48a3c-70a2-4797-a54d-b319bc326cd5 · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 7

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Observation a61be7d3-f5fd-4f5b-ac9e-114d5a8a0dd9 · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 8

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Observation 2f06a34a-c241-4e36-808f-80936a8fc30b · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 9

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Observation d2cae8d2-ca2e-4fa6-9d74-908bbb13b415 · outbound

This paper cites Karapetkov, H.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Karapetkov, H

Reference 10

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source=pdf_text observed=2026-06-29T18:06:55.696400Z digest=sha256:fa0500b178b0249203c8aab0dcd71b3018f13ba2ae1dcb4d7244f50359898801

Observation a64ca769-00d8-49de-8734-fa838f48950d · outbound

This paper cites Hickey, S.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Hickey, S

Reference 11

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Observation e9821bd2-11de-49a5-8192-91416f162c9e · outbound

This paper cites Bendjaballah, M.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Bendjaballah, M

Reference 12

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Observation 52724d1c-83d9-43c0-9f24-88d4adf42980 · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 13

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Observation a6f720d0-4bba-4862-bcc8-a5fdc99e192e · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 14

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Observation 245763dd-f7fa-4d04-a323-f4e82b6a8a91 · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 15

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Observation e1b73f71-9d07-4987-80cf-b820769f9ee8 · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 16

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Observation 523213ae-d868-402e-b749-359ad0e750b6 · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 17

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Observation f237e661-288c-4421-9cd8-63ab87c50490 · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 18

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Observation 3c00f8ea-95ea-41b1-a36e-fb84a6a519e1 · outbound

This paper cites Hashemi, J.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Hashemi, J

Reference 19

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Observation 67a05ee0-8988-4be4-affb-d5baf566d38f · outbound

This paper cites Koutsoupakis, D.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Koutsoupakis, D

Reference 20

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Observation 6d5108cc-7681-499f-ac11-080aefc463ba · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 21

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Observation 873959aa-dfb1-4a35-8ced-12ef060b01c9 · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 22

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Observation 8da630f8-65d5-4014-9603-ca97da859217 · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 23

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Observation ea455cd0-4f51-48b5-a735-575ccd077aed · outbound

This paper cites Huang, G.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Huang, G

Reference 24

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Observation 20334eac-775b-4816-b8e6-452bb23a0d2b · outbound

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High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 25

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Observation c749a727-39b9-43be-8cc2-20129aa2c486 · outbound

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High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 26

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Observation 14a508e6-3451-4208-b1f4-a794456d13cd · outbound

This paper cites Bakhshan, S.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Bakhshan, S

Reference 27

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arxiv_id, observed 2026-06-29T18:13:48.934166Z

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Observation ec5dd0a1-00c1-4b87-a8c9-cbd40db41aea · outbound

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High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 28

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Observation 062ea2a8-d566-4feb-9e55-3734c3350bb1 · outbound

This paper cites A graph neural network surrogate model for mesh-based crashworthiness prediction of vehicle panel components.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention A graph neural network surrogate model for mesh-based crashworthiness prediction of vehicle panel components

Reference 29

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Observation f912a97c-4836-4f95-86a4-114af61e2163 · outbound

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High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 30

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Observation 309b3a9b-8649-46d0-b37a-9577c50291d3 · outbound

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High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 31

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Observation 03f76fed-1ca5-4a1e-b580-2c72a78f42c1 · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Fourier Neural Operator for Parametric Partial Differential Equations

Reference 32

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Observation df124c2e-bfff-47a9-a6bb-4cf57ee90a83 · outbound

This paper cites A., Chavare, S., Akhare, D., Ranade, R., Cherukuri, R., and Tadepalli, S.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention A., Chavare, S., Akhare, D., Ranade, R., Cherukuri, R., and Tadepalli, S

Reference 33

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Observation 781efb9e-787a-463c-bde5-e9499ad5fbbe · outbound

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High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 34

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Observation c90ae161-8948-4551-9be9-8583919284b6 · outbound

This paper cites Transformer for Partial Differential Equations' Operator Learning.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Transformer for Partial Differential Equations' Operator Learning

Reference 35

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Observation 80273824-7dc3-4259-87cb-ffdbb43dcc28 · outbound

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High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 36

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Observation dca5e308-4541-456e-9105-8818280bbd6c · outbound

This paper cites Transolver: A Fast Transformer Solver for PDEs on General Geometries.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Transolver: A Fast Transformer Solver for PDEs on General Geometries

Reference 37

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Observation 03d366e0-8f9b-4c83-90a0-d976607b7800 · outbound

This paper cites an unresolved cited work.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Unresolved cited work

Reference 38

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arxiv_id, observed 2026-06-29T18:13:48.943812Z

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This paper cites DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations

Reference 39

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arxiv_id, observed 2026-06-29T18:13:48.949809Z

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.

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Observation 82e67419-85c9-4256-a9de-71494e79090b · outbound

This paper cites Accessed: October 8, 2025).

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Accessed: October 8, 2025)

Reference 40

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2a2d3f43-c684-409b-b17c-77d1c55571b5 · outbound

This paper cites Muon is Scalable for LLM Training.

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention Muon is Scalable for LLM Training

Reference 41

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verified exact
local_arxiv, observed 2026-06-29T18:13:48.947357Z

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.

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Pith citing papers

Observation e02a8460-dffb-42a9-aa37-d711fbd80146 · inbound

Uncertainty Quantification for AI-Driven Crash Simulation Surrogates: A Comparative Study of Monte Carlo Dropout and Deep Ensemble on Open-Source Bumper Beam Benchmark cites this paper.

Uncertainty Quantification for AI-Driven Crash Simulation Surrogates: A Comparative Study of Monte Carlo Dropout and Deep Ensemble on Open-Source Bumper Beam Benchmark High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention

Reference 4

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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