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Paper Citation Record · LEDGER

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates

As of 18 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2607.17297.

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

pith.paper-citation-record.v1
2607.17297 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T18:29:57.345898Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

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External citation measurements

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Outbound references

Observation e1265814-49ee-478e-8d5d-6fa613b1604f · outbound

This paper cites Journal of Mechanical Design , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Journal of Mechanical Design , volume=

Reference 1

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source=arxiv_source observed=2026-08-01T18:29:52.508531Z digest=sha256:9db9439ef408e0e1998c12111bda7f7d5c2476bfab33ecfe39625723bca140fc

Observation 3facbcc3-90a4-4bc8-8985-591ef3556757 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Advances in Neural Information Processing Systems , volume=

Reference 2

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source=arxiv_source observed=2026-08-01T18:29:52.627300Z digest=sha256:7ea6f5a1f7734aa6aa708878f0c26a2bc1c5634a99f69175155d37934b601035

Observation 341881a4-8cda-459f-b11b-63ea640ed68b · outbound

This paper cites DrivAerML: High-Fidelity Computational Fluid Dynamics Dataset for Road-Car External Aerodynamics.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates DrivAerML: High-Fidelity Computational Fluid Dynamics Dataset for Road-Car External Aerodynamics

Reference 3

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source=arxiv_source observed=2026-08-01T18:29:52.855919Z digest=sha256:c99d0c8bac2884d29a03af0e3e8aac7c488c6f80bf6842c30cf83a5bb3c2d66d

Observation d34c9c54-4c4c-46cd-8af1-13037d8dbeed · outbound

This paper cites Nature machine intelligence , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Nature machine intelligence , volume=

Reference 4

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source=arxiv_source observed=2026-08-01T18:29:53.018986Z digest=sha256:02d7b1854c6016727322aed95a50f69bd2c567b28f5110191afa0aadeaa39f6d

Observation 1c4e3fc9-f034-4187-b5b4-8d150aeb3ffd · outbound

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

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Fourier Neural Operator for Parametric Partial Differential Equations

Reference 5

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source=arxiv_source observed=2026-08-01T18:29:53.181106Z digest=sha256:2cf1a62c3f272f68f19f951dc2b13d04430fc9e4505e2b9c9cab448af6e7e2a8

Observation 5b92921c-0e9b-43b2-b85d-2d9a0ce10e15 · outbound

This paper cites Engineering Applications of Artificial Intelligence , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Engineering Applications of Artificial Intelligence , volume=

Reference 6

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source=arxiv_source observed=2026-08-01T18:29:53.314774Z digest=sha256:1705b2aad4e1d922b0f2ee95cffb0a9648d2166882c4de0991e8821cd1db888b

Observation bb6d1bbe-5bca-4762-a098-7032dcf91d7e · outbound

This paper cites Sequential Deep Operator Networks (.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Sequential Deep Operator Networks (

Reference 7

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source=arxiv_source observed=2026-08-01T18:29:53.481337Z digest=sha256:58a7ceea40f6594555af9eaad2b856da74b1fa173daf9c6a91cca17c7997814c

Observation 6e86ca23-2127-432a-a2d9-3af090121e53 · outbound

This paper cites Engineering Applications of Artificial Intelligence , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Engineering Applications of Artificial Intelligence , volume=

Reference 8

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source=arxiv_source observed=2026-08-01T18:29:53.618619Z digest=sha256:fbcfed0fe2824290cecd0dfa4f7847b6ec218fe265b8487799e5666484394444

Observation e12dafe8-eef4-4001-af65-e49865062e87 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Advances in Neural Information Processing Systems , volume=

Reference 9

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source=arxiv_source observed=2026-08-01T18:29:53.780383Z digest=sha256:b903abff59b4746339f590c3e478c88c5ad559269eb20ad351bf010912bac0f4

Observation 3d40d597-e7e1-4f5d-b8dd-86548e26f9cd · outbound

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

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations

Reference 10

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source=arxiv_source observed=2026-08-01T18:29:53.874068Z digest=sha256:51496ef046ad235db224a36fa203e7fba9b05f5a9f78f299b6f6ac7b0845244b

Observation c33da1c8-bdb4-4cf3-b453-cf3e70ae1ab7 · outbound

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

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Transolver: A Fast Transformer Solver for PDEs on General Geometries

Reference 11

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source=arxiv_source observed=2026-08-01T18:29:53.979698Z digest=sha256:4f138f8e1ad7e77752a1b9c3979659793ed91ac5ba3e5d56120910db33c94b6f

Observation a5800547-2acc-4137-b4a7-531f5cc92269 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Advances in Neural Information Processing Systems , volume=

Reference 12

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source=arxiv_source observed=2026-08-01T18:29:54.080920Z digest=sha256:6dfb8cac6a54b3090edb10b41a5965e003f0168260493b8e5c5a4489e267bf5c

Observation c7127cfd-225b-4fc1-9a61-97af46d05947 · outbound

This paper cites arXiv preprint arXiv:2502.09692 , year=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates arXiv preprint arXiv:2502.09692 , year=

Reference 13

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source=arxiv_source observed=2026-08-01T18:29:54.216174Z digest=sha256:0704269c917a21248988917907d20683e8f3302711ae04550a4e44701d557817

Observation 7d1b9038-a2fb-4734-96b9-4b1323e7ee5e · outbound

This paper cites Journal of Computational Physics , pages=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Journal of Computational Physics , pages=

Reference 14

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source=arxiv_source observed=2026-08-01T18:29:54.395441Z digest=sha256:1a021204702a9678ac95a1ff9b5dbdd2a41b733db18dfce97443629554c4af4a

Observation dd3247ce-b1cd-4f99-9214-05cdfde816be · outbound

This paper cites Forty-third International Conference on Machine Learning , year=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Forty-third International Conference on Machine Learning , year=

Reference 15

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source=arxiv_source observed=2026-08-01T18:29:54.561062Z digest=sha256:ce344ca25e5799179fd6b8007ecfbf602f3e2c6fd9db03329fcdab59bccf6d60

Observation aad34eda-6897-499e-8c7c-d5c77823644d · outbound

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

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates GeoTransolver: Learning Physics on Irregular Domains Using Multi-scale Geometry Aware Physics Attention Transformer

Reference 16

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source=arxiv_source observed=2026-08-01T18:29:54.701681Z digest=sha256:6ed23900dfc0cebbccc8e4be246b12fec3aa567463fe6603a8ebdce8eb0a13c7

Observation 92c159bc-437e-41a0-b018-608f10f4fe16 · outbound

This paper cites 2005 , publisher=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates 2005 , publisher=

Reference 17

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source=arxiv_source observed=2026-08-01T18:29:54.804744Z digest=sha256:cc4964ff23c418de1dec27d9b39bf8ee004e40449729d18ed3d02d1ca6d05083

Observation acdf75e8-f3b8-4262-88cc-6cf325dae5bb · outbound

This paper cites , author=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates , author=

Reference 18

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source=arxiv_source observed=2026-08-01T18:29:54.913914Z digest=sha256:c6def8f48c4d6e068348bca709e5095165f09e12b95f643967cb90c2f8d27e50

Observation a731ec2d-bbaf-4e40-9500-3f71874e8910 · outbound

This paper cites A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

Reference 19

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source=arxiv_source observed=2026-08-01T18:29:55.047344Z digest=sha256:805f611761ef46c468180769667d0a5b659701d48c3a69aa0fbee135c8e56658

Observation 05e12f67-0fd7-4a0b-ace4-07240ae5e011 · outbound

This paper cites Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction

Reference 20

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source=arxiv_source observed=2026-08-01T18:29:55.210693Z digest=sha256:ccce4ae0698a02b91ac2cd317d4840a38406549ee3efddfb1d208fb88e4f6a4c

Observation 25ccdd9f-6d28-4561-b3e6-c590f63da8e2 · outbound

This paper cites Physica D: Nonlinear Phenomena , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Physica D: Nonlinear Phenomena , volume=

Reference 21

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source=arxiv_source observed=2026-08-01T18:29:55.362681Z digest=sha256:db11123367ec29424cc225eba25cc0669fca04a55e7bd4ce9198bea0017c9630

Observation f98aa434-7ea1-454b-a602-4fdfe28063cf · outbound

This paper cites Machine Learning: Science and Technology , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Machine Learning: Science and Technology , volume=

Reference 22

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source=arxiv_source observed=2026-08-01T18:29:55.521087Z digest=sha256:615c096f298a23b1e5b73060e5e61b5d8bcdec990a1db9fc7e80231a87fe485a

Observation 1fb4fd2f-3aed-435b-9a4a-a3acb840c09b · outbound

This paper cites Conformal Prediction on Quantifying Uncertainty of Dynamic Systems.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Conformal Prediction on Quantifying Uncertainty of Dynamic Systems

Reference 23

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source=arxiv_source observed=2026-08-01T18:29:55.644488Z digest=sha256:d9e2c81e37267e6575e84a1207015864bf0ce10990f7a9f04dd864e64deee886

Observation 9a468e93-4804-4436-917b-2e7bfb8b16f0 · outbound

This paper cites 2012 , institution=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates 2012 , institution=

Reference 24

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source=arxiv_source observed=2026-08-01T18:29:55.770122Z digest=sha256:c295ce09743d50aafddb95d793307eeac95b420710d7b548b0dac976f80da9b9

Observation 8278d769-d4c2-452c-8a71-996ac7885ba6 · outbound

This paper cites International conference on machine learning , pages=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates International conference on machine learning , pages=

Reference 25

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Observation 7f471b27-6155-4ca7-9c64-ec494ac3e5d2 · outbound

This paper cites international conference on machine learning , pages=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates international conference on machine learning , pages=

Reference 26

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Observation 824471d6-b4a4-45aa-a042-11d7871d826d · outbound

This paper cites Advances in neural information processing systems , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Advances in neural information processing systems , volume=

Reference 27

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Observation 223b7aa9-154e-4711-a5b1-9d5320dcc2d3 · outbound

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Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Unresolved cited work

Reference 28

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source=arxiv_source observed=2026-08-01T18:29:56.243420Z digest=sha256:388d71fa739fbbd0daa2a2680af4a5771a4ab49a10a6278a4d5648697c5319c8

Observation f3edaeb7-93b1-4544-9cd5-ada972e734d1 · outbound

This paper cites Advances in neural information processing systems , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Advances in neural information processing systems , volume=

Reference 29

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Observation 5ad33ff6-58cd-4b7d-a79a-ea9bfc7cf766 · outbound

This paper cites Engineering Applications of Artificial Intelligence , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Engineering Applications of Artificial Intelligence , volume=

Reference 30

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Observation e652c422-2785-47da-bc9e-521275ac5a44 · outbound

This paper cites Engineering Applications of Artificial Intelligence , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Engineering Applications of Artificial Intelligence , volume=

Reference 31

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Observation 25ef2241-440f-46f0-8a4b-78ec5cc92dee · outbound

This paper cites Engineering Applications of Artificial Intelligence , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Engineering Applications of Artificial Intelligence , volume=

Reference 32

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Observation a504b0f2-8ede-4e21-88d2-9bef0fbb23b8 · outbound

This paper cites Engineering Applications of Artificial Intelligence , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Engineering Applications of Artificial Intelligence , volume=

Reference 33

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Observation 289eb482-0235-4b19-b5a6-c818521fa03b · outbound

This paper cites arXiv preprint arXiv:2512.13069 , year=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates arXiv preprint arXiv:2512.13069 , year=

Reference 34

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Observation 59ed9414-4f56-40fd-8eee-a98655bafc86 · outbound

This paper cites The Annals of Statistics , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates The Annals of Statistics , volume=

Reference 35

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Observation b6ff38ea-45b3-4158-8465-46e7538961c9 · outbound

This paper cites Engineering Applications of Artificial Intelligence , volume=.

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates Engineering Applications of Artificial Intelligence , volume=

Reference 36

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source=arxiv_source observed=2026-08-01T18:29:57.345898Z digest=sha256:5ce21909cbf2d76c892fbe703355242e8cd9920dc120291162977cf30aa4797f

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