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Paper Citation Record · LEDGER

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions

As of 10 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2607.26467.

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

pith.paper-citation-record.v1
2607.26467 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T15:17:44.468670Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

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

40 of 40 outbound references displayed

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  • unresolved40
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  • malformed identifier0
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External citation measurements

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Outbound references

Observation 05c64c67-90fb-4d76-b1d6-8dedc4f8cecb · outbound

This paper cites Prediction based traffic management in a metropolitan area,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Prediction based traffic management in a metropolitan area,

Reference 1

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Observation 3ac08401-4396-43b7-a967-a7fe5f43b1ef · outbound

This paper cites Hybrid spatio-temporal graph convolutional network: Improving traffic prediction with navi- gation data,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Hybrid spatio-temporal graph convolutional network: Improving traffic prediction with navi- gation data,

Reference 2

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Observation e7f87abc-5808-4fb0-86f9-9ce4d55fd030 · outbound

This paper cites Deep multi-view spatial-temporal network for taxi demand prediction,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Deep multi-view spatial-temporal network for taxi demand prediction,

Reference 3

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Observation 676a7258-f337-4eef-8746-05405d739339 · outbound

This paper cites Largest: A benchmark dataset for large- scale traffic forecasting,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Largest: A benchmark dataset for large- scale traffic forecasting,

Reference 4

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Observation 95b040eb-8ee7-4cc3-9d6c-69b5e7abe717 · outbound

This paper cites Diffusion convolutional recurrent neural network: Data-driven traffic forecasting,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Diffusion convolutional recurrent neural network: Data-driven traffic forecasting,

Reference 5

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Observation b78180e0-b8c3-43b1-a69e-21c42c0e6c1b · outbound

This paper cites Deep spatio-temporal residual networks for citywide crowd flows prediction,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Deep spatio-temporal residual networks for citywide crowd flows prediction,

Reference 6

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Observation 671b9664-2f8c-4824-bced-75c6d473b04d · outbound

This paper cites Spatio-temporal graph convolutional net- works: A deep learning framework for traffic forecasting,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Spatio-temporal graph convolutional net- works: A deep learning framework for traffic forecasting,

Reference 7

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Observation 4019de91-f5e3-48c7-a432-41b8ab437500 · outbound

This paper cites Pdformer: Propagation delay-aware dynamic long-range transformer for traffic flow prediction,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Pdformer: Propagation delay-aware dynamic long-range transformer for traffic flow prediction,

Reference 8

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Observation d94d502a-afc8-4456-a5eb-f7037164aade · outbound

This paper cites Decoupled dynamic spatial-temporal graph neural network for traffic forecasting,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Decoupled dynamic spatial-temporal graph neural network for traffic forecasting,

Reference 9

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Observation 06ee5c9c-5e2f-4610-9b55-d624eb2cb31c · outbound

This paper cites Autostg: Neural architecture search for predictions of spatio-temporal graphs,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Autostg: Neural architecture search for predictions of spatio-temporal graphs,

Reference 10

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Observation d4f7380f-57fe-4732-96b3-dcfe08b1c83d · outbound

This paper cites Autocts: Automated correlated time series forecasting,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Autocts: Automated correlated time series forecasting,

Reference 11

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Observation c1134217-ff7c-4ebc-a167-4cc3bedec755 · outbound

This paper cites Autostf: Decoupled neural archi- tecture search for cost-effective automated spatio-temporal forecasting,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Autostf: Decoupled neural archi- tecture search for cost-effective automated spatio-temporal forecasting,

Reference 12

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Observation d23bb54f-7375-45ce-9ef6-33045de662ad · outbound

This paper cites Darts: Differentiable architec- ture search,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Darts: Differentiable architec- ture search,

Reference 13

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Observation e3517b2f-abc7-456a-b5d8-567c3c09e374 · outbound

This paper cites Autost: Efficient neural architecture search for spatio-temporal prediction,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Autost: Efficient neural architecture search for spatio-temporal prediction,

Reference 14

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Observation f272f1e0-e35a-49b5-b65a-817f959f4e4e · outbound

This paper cites Autostg+: An automatic framework to discover the optimal network for spatio- temporal graph prediction,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Autostg+: An automatic framework to discover the optimal network for spatio- temporal graph prediction,

Reference 15

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Observation 21cc9639-9b6d-4a38-848a-acfb31033d9d · outbound

This paper cites Autostl: Automated spatio-temporal multi-task learning,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Autostl: Automated spatio-temporal multi-task learning,

Reference 16

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Observation 03159d1b-3096-4da1-bf3f-745d4db82209 · outbound

This paper cites Traffic spatial-temporal prediction based on neural architecture search,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Traffic spatial-temporal prediction based on neural architecture search,

Reference 17

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Observation f3add8ac-a93e-4f15-9fe4-1684e5690453 · outbound

This paper cites Evolutionary neural architecture search for traffic forecasting,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Evolutionary neural architecture search for traffic forecasting,

Reference 18

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Observation 99a559bd-ce60-4407-8ace-fad956b3cce8 · outbound

This paper cites Low cost evolutionary neural architecture search (LENAS) applied to traffic forecasting,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Low cost evolutionary neural architecture search (LENAS) applied to traffic forecasting,

Reference 19

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Observation d2632ae7-d8c6-479b-9f6a-c2d0e24d8f8f · outbound

This paper cites Au- tocts+: Joint neural architecture and hyperparameter search for correlated time series forecasting,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Au- tocts+: Joint neural architecture and hyperparameter search for correlated time series forecasting,

Reference 20

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Observation 61dac5bf-1d95-4f7b-9c2e-eaeb8c7481b6 · outbound

This paper cites Neural architecture search: A survey,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Neural architecture search: A survey,

Reference 21

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Observation f0117918-a519-44d1-ae1d-0cedbfe38156 · outbound

This paper cites Neural Architecture Search: Insights from 1000 Papers.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Neural Architecture Search: Insights from 1000 Papers

Reference 22

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Observation eb0d62d8-f2ef-4257-8361-19d03305e8f1 · outbound

This paper cites Graph neural network for traffic forecasting: A survey,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Graph neural network for traffic forecasting: A survey,

Reference 23

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Observation 84287a92-5836-4b84-8d02-a9a31733e42f · outbound

This paper cites Spatio-temporal graph neural networks for predictive learning in urban computing: A survey,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Spatio-temporal graph neural networks for predictive learning in urban computing: A survey,

Reference 24

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Observation 2f1966ba-94e4-49bd-ad91-7add162ab5d5 · outbound

This paper cites A comprehensive review of traffic prediction: From traditional machine learning to automl,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions A comprehensive review of traffic prediction: From traditional machine learning to automl,

Reference 25

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Observation b19a6fcf-9c3d-4b64-8f41-b4ca747dc23f · outbound

This paper cites Spatio-temporal self-supervised learning for traffic flow prediction,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Spatio-temporal self-supervised learning for traffic flow prediction,

Reference 26

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Observation 685273ab-41bb-4f52-a7af-d3a0a174691a · outbound

This paper cites Multi-modality spatio- temporal forecasting via self-supervised learning,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Multi-modality spatio- temporal forecasting via self-supervised learning,

Reference 27

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Observation 4a5ac304-7fc6-475f-bf9f-00f4dfcda40e · outbound

This paper cites Efficient large-scale traffic forecasting with transformers: A spatial data management perspective,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Efficient large-scale traffic forecasting with transformers: A spatial data management perspective,

Reference 28

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Observation b8fcf9f8-17f4-4c0b-af01-292d9d9e0652 · outbound

This paper cites Sagdfn: A scalable adaptive graph diffusion forecasting network for multivariate time series forecasting,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Sagdfn: A scalable adaptive graph diffusion forecasting network for multivariate time series forecasting,

Reference 29

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Observation 0c0af6c1-fe20-4ed0-b085-f2738a9af7b0 · outbound

This paper cites Traffic prediction with transfer learning: A mutual information-based approach,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Traffic prediction with transfer learning: A mutual information-based approach,

Reference 30

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Observation 3c9d45ec-876a-4490-abeb-7fcb07a27932 · outbound

This paper cites Personalized federated learning for cross-city traffic prediction,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Personalized federated learning for cross-city traffic prediction,

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Observation 4d38cd78-3a0f-493a-8230-7304d9688505 · outbound

This paper cites Diffstg: Probabilistic spatio-temporal graph forecasting with denoising diffusion models,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Diffstg: Probabilistic spatio-temporal graph forecasting with denoising diffusion models,

Reference 32

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Observation a4393e14-2b7d-4baa-9ad4-c2f9bec1399e · outbound

This paper cites Unist: A prompt-empowered universal model for urban spatio-temporal prediction,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Unist: A prompt-empowered universal model for urban spatio-temporal prediction,

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Observation 00b76fdc-43f1-422d-acb0-d7e526fc5b21 · outbound

This paper cites Opencity: Open spatio-temporal foundation models for traffic prediction,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Opencity: Open spatio-temporal foundation models for traffic prediction,

Reference 34

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Observation d85f4022-ef0f-4cac-830f-0b5eaaca5a96 · outbound

This paper cites Advances in neural architecture search,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Advances in neural architecture search,

Reference 35

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Observation bb990873-16bd-4757-a1fa-c010869398e8 · outbound

This paper cites Iot data analytics in dynamic environments: From an automated machine learning perspective,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Iot data analytics in dynamic environments: From an automated machine learning perspective,

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Observation c981387c-5d12-49d3-b16c-d18cfee52072 · outbound

This paper cites Optimizing time series forecasting architec- tures: A hierarchical neural architecture search approach,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Optimizing time series forecasting architec- tures: A hierarchical neural architecture search approach,

Reference 37

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Observation 80bcf3c8-f98f-4295-b47f-33861c59370f · outbound

This paper cites Neural architecture search with reinforcement learning,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Neural architecture search with reinforcement learning,

Reference 38

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Observation b906c992-4b0e-4903-b5dc-6e4e853f424f · outbound

This paper cites Differentiable archi- tecture search with random features,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Differentiable archi- tecture search with random features,

Reference 39

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Observation 716321b2-523d-49fd-9491-ee30414a9909 · outbound

This paper cites Zero-cost operation scoring in differentiable architecture search,.

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions Zero-cost operation scoring in differentiable architecture search,

Reference 40

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