Paper Citation Record · LEDGER

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting

As of 20 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2508.00884.

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

pith.paper-citation-record.v1
2508.00884 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:06:55.022657Z

measured 44 of 44 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 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

44 of 44 outbound references displayed

verified exact0
verified fuzzy24
unresolved20
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 82074311-2858-45aa-acbc-13bb791bdfc0 · outbound

This paper cites an unresolved cited work.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:06:55.660683Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6a045597-1915-431c-ad3a-50e889368aad · outbound

This paper cites Accurate freeway travel time prediction with state-space neural networks under missing data,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Accurate freeway travel time prediction with state-space neural networks under missing data,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.647193Z

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.

Observation b7f815af-6c81-4f15-a246-730080f1f701 · outbound

This paper cites Multivariate vehicular traffic flow prediction: evalua- tion of arimax modeling,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Multivariate vehicular traffic flow prediction: evalua- tion of arimax modeling,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.634219Z

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.

Observation 5b4cc267-830f-4267-b087-0fc3474398b4 · outbound

This paper cites Graph Neural Networks in Intelligent Transportation Systems: Advances, Applications and Trends.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Graph Neural Networks in Intelligent Transportation Systems: Advances, Applications and Trends

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.855132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b80cea6-7291-4fb2-b386-85ef95df986b · outbound

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

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Graph neural network for traffic forecasting: A survey,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.860023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c794a53-8f55-4e58-a365-a820b0f35c3c · outbound

This paper cites Graph neural network for traffic forecasting: The research progress,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Graph neural network for traffic forecasting: The research progress,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.612894Z

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.

Observation 80f17e35-8df9-4df1-8612-43413e3d73c8 · outbound

This paper cites Modeling and forecasting vehicular traffic flow as a seasonal arima process: Theoretical basis and empirical results,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Modeling and forecasting vehicular traffic flow as a seasonal arima process: Theoretical basis and empirical results,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.868885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cceb3e1b-93f7-4bfb-b1a4-a45317b8f621 · outbound

This paper cites Travel-time prediction with sup- port vector regression,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Travel-time prediction with sup- port vector regression,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.591774Z

Source-reported events for the cited work

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Observation bf7eeba3-5753-4390-b2da-09e969f3e20e · outbound

This paper cites Traffic flow forecasting by seasonal svr with chaotic simulated annealing algorithm,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Traffic flow forecasting by seasonal svr with chaotic simulated annealing algorithm,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.578708Z

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.

Observation 5ecdd86b-b414-49fb-b73f-27114fc9c4c5 · outbound

This paper cites Traffic flow prediction using adaboost algo- rithm with random forests as a weak learner,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Traffic flow prediction using adaboost algo- rithm with random forests as a weak learner,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.565332Z

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.

Observation ad58905a-bf4d-4abd-8aae-a37e5e7e97aa · outbound

This paper cites A gradient boosting method to improve travel time prediction,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting A gradient boosting method to improve travel time prediction,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.884468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66922b59-b4bb-47f9-a65d-7db0281f5360 · outbound

This paper cites High-order gaussian process dynamical models for traffic flow prediction,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting High-order gaussian process dynamical models for traffic flow prediction,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.544114Z

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.

Observation 0100a7e8-de72-465d-82b3-9f67dba7da76 · outbound

This paper cites Short-term traffic state prediction based on temporal–spatial correlation,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Short-term traffic state prediction based on temporal–spatial correlation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.530626Z

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.

Observation fbe3b86a-e52f-442d-9db2-32d32322e797 · outbound

This paper cites A bayesian network approach to traffic flow forecasting,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting A bayesian network approach to traffic flow forecasting,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.517484Z

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.

Observation 869fc486-5d04-4496-8e1d-40927810c0bc · outbound

This paper cites Traffic flow prediction with big data: A deep learning approach,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Traffic flow prediction with big data: A deep learning approach,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.900121Z

Source-reported events for the cited work

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Observation 1ff20dfe-fddb-4076-a5c6-406a3d099ae3 · outbound

This paper cites Long short-term memory neural network for traffic speed prediction using remote microwave sensor data,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Long short-term memory neural network for traffic speed prediction using remote microwave sensor data,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.903891Z

Source-reported events for the cited work

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Observation 12fcb4ac-2a38-40cb-b25e-60148c9e09c2 · outbound

This paper cites Using lstm and gru neural network methods for traffic flow prediction,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Using lstm and gru neural network methods for traffic flow prediction,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.487387Z

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.

Observation 7edda022-0408-4352-985c-73b923d51914 · outbound

This paper cites Spatiotemporal recurrent convolutional networks for traffic prediction in transportation networks,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Spatiotemporal recurrent convolutional networks for traffic prediction in transportation networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.473784Z

Source-reported events for the cited work

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Observation 5516db96-718b-480a-89e2-0db8db418334 · outbound

This paper cites Convolutional lstm network: A machine learning approach for precipitation nowcasting,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Convolutional lstm network: A machine learning approach for precipitation nowcasting,

Reference 19

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Source-reported events for the cited work

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Observation 438d4ac3-5219-454f-8d61-b36d67364fcd · outbound

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

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Deep spatio-temporal residual networks for citywide crowd flows prediction,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.920347Z

Source-reported events for the cited work

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Observation db8627a7-d5e5-46f1-90d3-0bbb688b7eb1 · outbound

This paper cites Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.443669Z

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.

Observation 65a4bd04-c318-40e9-a2b2-d808da572d3f · outbound

This paper cites Short-term traffic flow forecasting with spatial-temporal correlation in a hybrid deep learning framework.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Short-term traffic flow forecasting with spatial-temporal correlation in a hybrid deep learning framework

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.928586Z

Source-reported events for the cited work

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Observation 67984841-84d1-4cc8-9f45-87a52cc66747 · outbound

This paper cites Attention based spatial- temporal graph convolutional networks for traffic flow forecasting,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Attention based spatial- temporal graph convolutional networks for traffic flow forecasting,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.936723Z

Source-reported events for the cited work

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Observation 429fc774-cdfe-4fb1-8a64-de6f0899f93e · outbound

This paper cites Graph WaveNet for Deep Spatial-Temporal Graph Modeling.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Graph WaveNet for Deep Spatial-Temporal Graph Modeling

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.941466Z

Source-reported events for the cited work

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Observation e7879230-48df-4160-832f-a8144e861e7e · outbound

This paper cites Attention is all you need,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Attention is all you need,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.946710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2213a61d-3294-44b1-89b1-261d010a4d0f · outbound

This paper cites Gman: A graph multi-attention network for traffic prediction,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Gman: A graph multi-attention network for traffic prediction,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.950848Z

Source-reported events for the cited work

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Observation 862159b8-015e-48e1-a673-96aa43be6af5 · outbound

This paper cites Spatial-Temporal Transformer Networks for Traffic Flow Forecasting.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Spatial-Temporal Transformer Networks for Traffic Flow Forecasting

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.955367Z

Source-reported events for the cited work

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Observation 370eee67-8b49-481e-bf1f-f1184ad95b73 · outbound

This paper cites A multi-layer model based on transformer and deep learning for traffic flow prediction,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting A multi-layer model based on transformer and deep learning for traffic flow prediction,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.405113Z

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.

Observation f1b93db6-8d6e-4991-9949-46387d971ce1 · outbound

This paper cites Traffic transformer: Capturing the continuity and periodicity of time series for traffic forecasting,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Traffic transformer: Capturing the continuity and periodicity of time series for traffic forecasting,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.391360Z

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.

Observation f820f3ff-58f0-4028-a143-8535fe103b33 · outbound

This paper cites Spatial-temporal synchronous graph convolutional networks: A new framework for spatial-temporal network data forecasting,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Spatial-temporal synchronous graph convolutional networks: A new framework for spatial-temporal network data forecasting,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.376339Z

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.

Observation e858466b-5c2a-4614-944c-bb913ec0d1d0 · outbound

This paper cites Short-term traffic speed forecasting based on graph attention temporal convolutional networks,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Short-term traffic speed forecasting based on graph attention temporal convolutional networks,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.363321Z

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.

Observation bbd7a18c-cf36-471d-a712-ab5eb0502fc1 · outbound

This paper cites St-grat: A novel spatio-temporal graph attention networks for accurately forecasting dynamically changing road speed,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting St-grat: A novel spatio-temporal graph attention networks for accurately forecasting dynamically changing road speed,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.350108Z

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.

Observation 46776c74-742b-4cd3-976f-0d3c0ed7c80f · outbound

This paper cites Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

Reference 34

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Source-reported events for the cited work

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Observation e91a5b3c-6518-44bd-a961-eef79b3337b5 · outbound

This paper cites Learning convolutional neural networks for graphs,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Learning convolutional neural networks for graphs,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.336685Z

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.

Observation b79bd5f5-3a1a-4e4e-b59c-68f646372b65 · outbound

This paper cites Spatio-temporal graph convolution for skeleton based action recognition,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Spatio-temporal graph convolution for skeleton based action recognition,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.323573Z

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.

Observation ec71f01a-e62f-4053-8256-678534f00dee · outbound

This paper cites Convolutional neural networks on graphs with fast localized spectral filtering,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Convolutional neural networks on graphs with fast localized spectral filtering,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:54.991219Z

Source-reported events for the cited work

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Observation b1c39f3f-6e84-42ef-aa03-0c2403730e6c · outbound

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

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Spatio-temporal graph convolutional net- works: a deep learning framework for traffic forecasting,

Reference 38

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Source-reported events for the cited work

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Observation 7645e830-ee39-4856-9556-05929a5f35b7 · outbound

This paper cites Network level spatial temporal traffic forecasting with hierarchical-attention-lstm,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Network level spatial temporal traffic forecasting with hierarchical-attention-lstm,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.293266Z

Source-reported events for the cited work

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Observation 905c8574-eca6-42b6-b0a7-6aed35969fc1 · outbound

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

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Deep multi-view spatial-temporal network for taxi demand prediction,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.280087Z

Source-reported events for the cited work

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Observation c85e0517-56bb-4891-afd0-b25db02016a3 · outbound

This paper cites Batch normalization: accelerating deep net- work training by reducing internal covariate shift,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Batch normalization: accelerating deep net- work training by reducing internal covariate shift,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.266602Z

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.

Observation f5b67621-5c0b-4b47-8beb-949fec22b809 · outbound

This paper cites Dropout: a simple way to prevent neural networks from overfit- ting,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Dropout: a simple way to prevent neural networks from overfit- ting,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.251742Z

Source-reported events for the cited work

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Observation c46cd5d7-48d7-40f9-b05a-902de364932e · outbound

This paper cites Do transformers really perform badly for graph representation?.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Do transformers really perform badly for graph representation?

Reference 43

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Observation 1f340773-3f41-4628-a5b0-95b30daf756f · outbound

This paper cites Towards deep learning models resistant to adversarial attacks,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Towards deep learning models resistant to adversarial attacks,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T18:06:55.018606Z

Source-reported events for the cited work

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Observation 68bbd656-98a7-46e2-9812-777c5141ea6e · outbound

This paper cites Graph foundation models: Concepts, opportunities and challenges,.

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting Graph foundation models: Concepts, opportunities and challenges,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:06:55.221827Z

Source-reported events for the cited work

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