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Paper Citation Record · LEDGER

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention

As of 9 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 2 inbound Pith citation observations for arXiv:2512.13758.

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

pith.paper-citation-record.v1
2512.13758 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T16:29:50.179816Z

measured 27 of 27 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T23:12:17.759955Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T20:03:56.415449Z

Reference resolution

25 of 25 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved22
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 70c92e0e-8a0f-4f1a-a3a9-74f951ccefda · outbound

This paper cites Europe-wide high-spatial resolution air pollution models are improved by including traffic flow estimates on all roads,.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Europe-wide high-spatial resolution air pollution models are improved by including traffic flow estimates on all roads,

Reference 1

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Observation b941f236-91f7-4ded-80cd-0b7cda6429bb · outbound

This paper cites Empirical macroscopic fundamental diagrams: New insights from loop detector and floating car data,.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Empirical macroscopic fundamental diagrams: New insights from loop detector and floating car data,

Reference 2

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doi, observed 2026-08-03T16:33:28.461092Z

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Observation 5c7c4f2f-3405-4094-b8d2-a804666b8288 · outbound

This paper cites Estimating traffic flow rate on freeways from probe vehicle data and fundamental diagram,.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Estimating traffic flow rate on freeways from probe vehicle data and fundamental diagram,

Reference 3

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Observation e025e9b9-dc00-4660-a720-2a545b1835e7 · outbound

This paper cites Traffic flow estimation using probe vehicle data,.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Traffic flow estimation using probe vehicle data,

Reference 4

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Observation 96ef0449-fa02-4d40-af89-5a9aff4f7505 · outbound

This paper cites Multi-models machine learning methods for traffic flow estimation from Floating Car Data,.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Multi-models machine learning methods for traffic flow estimation from Floating Car Data,

Reference 5

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Observation 3b7f1fa3-6c64-44ed-b7cd-94371175a2f0 · outbound

This paper cites Network topological ef- fects on the macroscopic fundamental diagram,.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Network topological ef- fects on the macroscopic fundamental diagram,

Reference 6

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source=pdf_text observed=2026-08-03T16:29:48.075326Z digest=sha256:649feb910a3cc4c1de1e60dc8cdc7e9ad2ca46a7c2b9be9d321ff7e3a70fed73

Observation c5b55267-9ac5-43d8-a809-837b6fcee7ef · outbound

This paper cites DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction

Reference 7

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source=pdf_text observed=2026-08-03T16:29:48.203255Z digest=sha256:736ed1722925e05f3e4d38ab5162af63bc01387757c2ff8145b2b9ddd7ceb5be

Observation c3b06625-0e82-4b54-ac7d-81c9973b1987 · outbound

This paper cites Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey

Reference 8

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source=pdf_text observed=2026-08-03T16:29:48.283500Z digest=sha256:3abf9cc88cd75ab652c2ace3a6a32f8bd9782efec42a20ce56297bc8a9b53281

Observation ebc9366d-80fe-4be5-88dc-2b24c24aea76 · outbound

This paper cites Spatio-Temporal Graph Neural Networks: A Survey.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Spatio-Temporal Graph Neural Networks: A Survey

Reference 9

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source=pdf_text observed=2026-08-03T16:29:48.446623Z digest=sha256:3a89d6a260b1b12f13ed2e40ff5e2b91c7e8c62a6348c5205a29fab83023feef

Observation 003e3d6f-534a-438d-b5cb-41b869270890 · outbound

This paper cites Evaluating the Generalization Ability of Spatiotemporal Model in Urban Scenario.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Evaluating the Generalization Ability of Spatiotemporal Model in Urban Scenario

Reference 10

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source=pdf_text observed=2026-08-03T16:29:48.606912Z digest=sha256:5f48f88cc5b350bfdf0a3078b10e4635fd4010de4165753f5ebdb9b01e9fd216

Observation 94e451f5-c96f-454d-9436-432937793e55 · outbound

This paper cites Inductive representation learning on large graphs,.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Inductive representation learning on large graphs,

Reference 11

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source=pdf_text observed=2026-08-03T16:29:48.714769Z digest=sha256:2d608bbac68bec6326688a97a6a101dfe54bc55674ae477354a709c5a2d398dd

Observation 89d1f2c1-66a5-43b5-b2ec-af357fcb3357 · outbound

This paper cites Comparison be- tween inductive and transductive learning in a real citation net- work using graph neural networks,.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Comparison be- tween inductive and transductive learning in a real citation net- work using graph neural networks,

Reference 12

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source=pdf_text observed=2026-08-03T16:29:48.795069Z digest=sha256:a6edfdb582cb76c8ee4c0cfeb432ea235e828dffd52e69b98da3bb112166719f

Observation d7a3225b-5d52-4e37-b6ba-3752390a543a · outbound

This paper cites Network-Wide Traffic Flow Estimation Across Multiple Cities with Global Open Multi-Source Data: A Large-Scale Case Study in Europe and North America.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Network-Wide Traffic Flow Estimation Across Multiple Cities with Global Open Multi-Source Data: A Large-Scale Case Study in Europe and North America

Reference 13

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source=pdf_text observed=2026-08-03T16:29:48.894442Z digest=sha256:17ef976a18733425c8dbbf226f0506c438129ef7eb86aaf61f62a2860af29d37

Observation e221cb00-8466-4a98-9635-9fd99666fe54 · outbound

This paper cites Network-wide Freeway Traffic Estimation Using Sparse Sensor Data: A Dirichlet Graph Auto-Encoder Approach.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Network-wide Freeway Traffic Estimation Using Sparse Sensor Data: A Dirichlet Graph Auto-Encoder Approach

Reference 14

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source=pdf_text observed=2026-08-03T16:29:49.022075Z digest=sha256:474e84f18aa88018438b2ba552cebeb8d6516079da31befda587b78bfaa87516

Observation 34afb4a3-30ab-4f36-868f-ee73f09b584c · outbound

This paper cites Urban Network-Wide Traffic V olume Estimation Under Sparse De- ployment of Detectors,.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Urban Network-Wide Traffic V olume Estimation Under Sparse De- ployment of Detectors,

Reference 15

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source=pdf_text observed=2026-08-03T16:29:49.142064Z digest=sha256:88abd57b2d5ac3092ae414e68eb0da45bd8925a9bd73da8e99ff2bfbd0d45d3c

Observation 719f0d53-4af7-458a-b3ed-4168f24436e3 · outbound

This paper cites Network-Wide Traffic Flow Estimation with Insufficient V olume Detection and Crowdsourcing Data,.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Network-Wide Traffic Flow Estimation with Insufficient V olume Detection and Crowdsourcing Data,

Reference 16

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source=pdf_text observed=2026-08-03T16:29:49.248126Z digest=sha256:dfcdf7886f9cc3212ed6d175f2c512b30b44b77eee6cae9072c31dad9dfe2a9c

Observation 2a77019e-107f-4d69-ba6e-7c452322237e · outbound

This paper cites Towards better traffic volume estimation: Jointly addressing the underdetermination and nonequilibrium problems with correlation-adaptive GNNs.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Towards better traffic volume estimation: Jointly addressing the underdetermination and nonequilibrium problems with correlation-adaptive GNNs

Reference 17

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source=pdf_text observed=2026-08-03T16:29:49.357613Z digest=sha256:a5ad3bb78290faf5a13a7765230855ad34c71918706ae2cbc18ec7106e1a1093

Observation a5e6d9b5-b525-4356-921f-1ae8c70af213 · outbound

This paper cites Graph attention networks,.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Graph attention networks,

Reference 18

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source=pdf_text observed=2026-08-03T16:29:49.503351Z digest=sha256:976bcbbe7b5fe9b82e99d43d6f60de7dbe778fedf8bf254e397d75b30dcfdf70

Observation 48b12f94-8fb6-4634-ba93-28418153e8da · outbound

This paper cites Semi-supervised classification with graph convolutional networks,.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Semi-supervised classification with graph convolutional networks,

Reference 19

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source=pdf_text observed=2026-08-03T16:29:49.630886Z digest=sha256:c0f37ad8fe841a567d1530ca9610f9558f1cf85f368aac7b1d6f1c636e7caab1

Observation 86284ec3-aa85-4b0e-b02e-f9df7beb162f · outbound

This paper cites Finite State Graphon Games with Applications to Epidemics.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Finite State Graphon Games with Applications to Epidemics

Reference 20

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source=pdf_text observed=2026-08-03T16:29:49.741073Z digest=sha256:be46815ac7a4fd175722f22bf41c5498a75af24697f43a795b77ba7a4f7d7e7b

Observation 14f7475a-0d9c-4d88-92cf-8b0af9cc5989 · outbound

This paper cites Representation Learning on Heterophilic Graph with Directional Neighborhood Attention.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Representation Learning on Heterophilic Graph with Directional Neighborhood Attention

Reference 21

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source=pdf_text observed=2026-08-03T16:29:49.854892Z digest=sha256:81f7a242788076d8df283105fe2ab91cb867ca4526b21c5fef2995b697488b6f

Observation bba09cb2-0c0b-4f5b-97e4-ca6f913d83fa · outbound

This paper cites Spatio-temporal Graph Con- volutional Networks: A Deep Learning Framework for Traffic Fore- casting.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Spatio-temporal Graph Con- volutional Networks: A Deep Learning Framework for Traffic Fore- casting

Reference 22

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source=pdf_text observed=2026-08-03T16:29:49.958162Z digest=sha256:0635402c481a3933b619169bd91029227d9962a85dcb4a333e5fe137ed9a8aec

Observation c37783e0-3de5-4686-b0e0-8196f974bf0f · outbound

This paper cites Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting

Reference 23

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source=pdf_text observed=2026-08-03T16:29:50.062862Z digest=sha256:219c43c1c53584c4b87d9542840cc949eb316b45371caaa3de24b96a01e68abc

Observation 76acdc8e-a0b2-4b8b-99f9-1055fa37cc03 · outbound

This paper cites PeMS: California Freeway Traffic Data.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention PeMS: California Freeway Traffic Data

Reference 24

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source=pdf_text observed=2026-08-03T16:29:50.175636Z digest=sha256:aaffc9c8ed703455dd838654866e4cefc78c4e50dbf9b7ff65386a13d946776e

Observation 74b81f57-f258-47a0-9fc8-a17fb72ba2ec · outbound

This paper cites an unresolved cited work.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Unresolved cited work

Reference 25

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source=pdf_text observed=2026-08-03T16:29:50.179816Z digest=sha256:45d2a224216b8f5efb9dea983d9269c2fa8033c3fac114634b4e50350c392799

Pith citing papers

Observation 61f59801-9df2-45c1-bdea-b0973f1e53b1 · inbound

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation cites this paper.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention

Reference 22

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T19:55:12.763334Z digest=sha256:c4f26f02342af90fea476de9bf351d0c5304c746872a9b1d71512824385665be

Observation 0991e046-ed40-4ac9-ab67-f9484a48deaf · inbound

Capacity-Aware Deep Learning for Generalizable Traffic Volume Estimation Across Links and Cities cites this paper.

Capacity-Aware Deep Learning for Generalizable Traffic Volume Estimation Across Links and Cities Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention

Reference 11

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source=pdf_text observed=2026-07-31T23:12:17.759955Z digest=sha256:bb25883c9602fe666d8d1a326cd92e45cdddbbdac39916858fbff4cabb153cc4