Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-02T03:30:46.395319Z
Paper Citation Record · LEDGER
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions
As of 9 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2607.13866.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
23 of 23 outbound references displayed
- verified exact2
- verified fuzzy0
- unresolved20
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 02d8c047-c8d8-437c-955f-8035b8846ea8 · outbound
This paper cites an unresolved cited work.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions Unresolved cited work
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:44.256696Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dd3f07d1-dc5f-414a-990e-c863e6a3fb33 · outbound
This paper cites URL:https://mlanthology.org/iclr/2022/brandstetter2022iclr-message/.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions URL:https://mlanthology.org/iclr/2022/brandstetter2022iclr-message/
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:44.404253Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d8677e0b-d355-4aa4-9678-6476c4ffa730 · outbound
This paper cites 72525–72624.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions 72525–72624
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:44.533443Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dfb8529b-4097-40b0-91ad-1ce845835a03 · outbound
This paper cites Liu, S., Yu, Y., Zhang, T., Liu, H., Liu, X., Meng, D.,.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions Liu, S., Yu, Y., Zhang, T., Liu, H., Liu, X., Meng, D.,
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:45.246765Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf47c15e-6146-47b0-8a61-a2e049c779ef · outbound
This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions Fourier Neural Operator for Parametric Partial Differential Equations
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:44.938294Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e7470a3-36ac-484d-b972-40b1c103425a · outbound
This paper cites Transformer for Partial Differential Equations' Operator Learning.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions Transformer for Partial Differential Equations' Operator Learning
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:45.167508Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9244558c-5959-4ce8-ba8e-2cf9bd42c29c · outbound
This paper cites Neurocomputing 648, 130518.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions Neurocomputing 648, 130518
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:45.339085Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 85beda34-7178-438a-8aec-12eb487fe169 · outbound
This paper cites 150039–150101.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions 150039–150101
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:45.550742Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a62475d-b345-4a97-b128-be3be96577aa · outbound
This paper cites DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:45.820864Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c78d4ea7-4ab9-434c-aa27-a45caad58195 · outbound
This paper cites doi:10.52202/075280-3376.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions doi:10.52202/075280-3376
Reference 19
- Resolution
- verified exact
- doi, observed 2026-08-02T03:33:32.783721Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f2fb1355-1250-410f-ad18-67976756327f · outbound
This paper cites V03BT03A049.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions V03BT03A049
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:46.024542Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 48ddc546-8f89-48d3-ba8d-3206fb17e582 · outbound
This paper cites Transolver: A Fast Transformer Solver for PDEs on General Geometries.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions Transolver: A Fast Transformer Solver for PDEs on General Geometries
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:46.140539Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f079ed18-9f6b-4464-9277-18a7d2467435 · outbound
This paper cites Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometries.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometries
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:46.230136Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1cf331d1-ea23-46d9-b6d4-36e35c2b6b14 · outbound
This paper cites an unresolved cited work.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions Unresolved cited work
Reference 72
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-02T03:30:46.395319Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2e57cdcc-b57a-4106-8bec-e5167d9a9f46 · outbound
This paper cites American Mathematical Society, Providence, Rhode Island.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions American Mathematical Society, Providence, Rhode Island
Reference 1998
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:44.489942Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e7086da5-6190-4e59-94bf-55ca49e0a266 · outbound
This paper cites Transolver++: An Accurate Neural Solver for PDEs on Million-Scale Geometries.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions Transolver++: An Accurate Neural Solver for PDEs on Million-Scale Geometries
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:45.443683Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 928eddc3-e2d5-4980-9686-6a50c0da4c93 · outbound
This paper cites Learning Mesh-Based Simulation with Graph Networks.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions Learning Mesh-Based Simulation with Graph Networks
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:45.650991Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 36b38f96-63aa-4cb6-8a0f-d1536918cfdc · outbound
This paper cites 24924–24940.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions 24924–24940
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:44.452293Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a0070705-0798-492c-9823-d37582eb03be · outbound
This paper cites 23463–23478.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions 23463–23478
Reference 2022
- Resolution
- verified exact
- doi, observed 2026-08-02T03:33:32.956036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 116cface-61a6-42d7-b7b3-2f0b2b2d3338 · outbound
This paper cites Aerospace Science and Technology 137, 108268.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions Aerospace Science and Technology 137, 108268
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:44.647903Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4d404dcc-0eb8-4b11-8b82-ae1efabf66b0 · outbound
This paper cites DrivAerML: High-Fidelity Computational Fluid Dynamics Dataset for Road-Car External Aerodynamics.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions DrivAerML: High-Fidelity Computational Fluid Dynamics Dataset for Road-Car External Aerodynamics
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:44.113507Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4d905a20-2fc9-46a6-a8aa-1873be06850b · outbound
This paper cites doi:10.2514/6.2025-0036.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions doi:10.2514/6.2025-0036
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:44.186949Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5da43c5d-a7eb-4e2d-a54b-0f29d2d36737 · outbound
This paper cites Computers & Fluids 308, 106979.
Evaluation of State-of-the-Art Deep Learning Architectures for Aerodynamical Predictions Computers & Fluids 308, 106979
Reference 2026
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T03:30:44.775814Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.