Paper Citation Record · LEDGER

Virtual Nodes Improve Long-term Traffic Prediction

As of 11 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2501.10048.

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

pith.paper-citation-record.v1
2501.10048 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:27:14.577199Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T01:10:24.579325Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

44 of 44 outbound references displayed

verified exact3
verified fuzzy26
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation b1e16524-8923-491f-8288-613052e14591 · outbound

This paper cites Long-term traffic prediction based on lstm encoder-decoder architecture.

Virtual Nodes Improve Long-term Traffic Prediction Long-term traffic prediction based on lstm encoder-decoder architecture

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.343082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation de083124-267d-429f-b37b-fe3d85ae1e00 · outbound

This paper cites Traffic flow forecasting for urban work zones.

Virtual Nodes Improve Long-term Traffic Prediction Traffic flow forecasting for urban work zones

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.322844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dc3aa0d4-9fb2-4d3c-a53e-a56bf6204ba1 · outbound

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

Virtual Nodes Improve Long-term Traffic Prediction Spatio-temporal graph convolutional networks: a deep learning framework for traffic forecasting

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.300986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4b495d85-da79-46b6-9470-0136eb7ef261 · outbound

This paper cites On the bottleneck of graph neural networks and its practical implications.

Virtual Nodes Improve Long-term Traffic Prediction On the bottleneck of graph neural networks and its practical implications

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.282980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3015992d-dae0-404a-a4bb-feeefcb1218a · outbound

This paper cites Oversquashing in gnns through the lens of information contraction and graph expansion.

Virtual Nodes Improve Long-term Traffic Prediction Oversquashing in gnns through the lens of information contraction and graph expansion

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.265635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 366f515e-cf59-421b-ade2-00c3343c3eb5 · outbound

This paper cites On over-squashing in message passing neural networks: The impact of width, depth, and topology.

Virtual Nodes Improve Long-term Traffic Prediction On over-squashing in message passing neural networks: The impact of width, depth, and topology

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.248439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 42048245-e8eb-4cec-86d3-087ce7600907 · outbound

This paper cites Learning Graph-Level Representation for Drug Discovery.

Virtual Nodes Improve Long-term Traffic Prediction Learning Graph-Level Representation for Drug Discovery

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-10T19:27:14.733123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 57d7fde0-22d3-4c61-9bb4-60eedd6498e3 · outbound

This paper cites Neural message passing for quantum chemistry.

Virtual Nodes Improve Long-term Traffic Prediction Neural message passing for quantum chemistry

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.395587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 539c9b67-c535-4702-8cc0-4424aa9b69cb · outbound

This paper cites Graph Classification via Deep Learning with Virtual Nodes.

Virtual Nodes Improve Long-term Traffic Prediction Graph Classification via Deep Learning with Virtual Nodes

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.400917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59ce9ea8-c4de-4dac-be4d-1c443e1c6aac · outbound

This paper cites Boosting graph structure learning with dummy nodes.

Virtual Nodes Improve Long-term Traffic Prediction Boosting graph structure learning with dummy nodes

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.217771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8fbf204f-6e8f-4d8e-92a5-4a73b49c8134 · outbound

This paper cites The graph neural network model.

Virtual Nodes Improve Long-term Traffic Prediction The graph neural network model

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.412895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1618c148-c24f-43a0-952a-f640a552bbf9 · outbound

This paper cites Inductive graph neural networks for spatiotemporal kriging.

Virtual Nodes Improve Long-term Traffic Prediction Inductive graph neural networks for spatiotemporal kriging

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.190889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b71392ba-a178-4e21-bc82-31e60555f6a8 · outbound

This paper cites Uncertainty quantification of sparse travel demand prediction with spatial-temporal graph neural networks.

Virtual Nodes Improve Long-term Traffic Prediction Uncertainty quantification of sparse travel demand prediction with spatial-temporal graph neural networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.423667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37976db6-91c4-498c-abf8-dd9af9da42cf · outbound

This paper cites Adaptive graph convolutional recurrent network for traffic forecasting.

Virtual Nodes Improve Long-term Traffic Prediction Adaptive graph convolutional recurrent network for traffic forecasting

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.428706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55844b3a-154f-4f80-8af2-1575e273683e · outbound

This paper cites Highly accurate protein structure prediction with alphafold.

Virtual Nodes Improve Long-term Traffic Prediction Highly accurate protein structure prediction with alphafold

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.433679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f30eaca-a68c-4f42-9f08-88cc320ff807 · outbound

This paper cites Graph neural networks for social recommendation.

Virtual Nodes Improve Long-term Traffic Prediction Graph neural networks for social recommendation

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.141655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 77e9be9a-f401-46df-81c3-98909ea58856 · outbound

This paper cites Lightgcn: Simplifying and powering graph convolution network for recommendation.

Virtual Nodes Improve Long-term Traffic Prediction Lightgcn: Simplifying and powering graph convolution network for recommendation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.125636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 325e44c7-a43d-4bd0-ab38-ae3bc4d231cf · outbound

This paper cites Long short-term memory.

Virtual Nodes Improve Long-term Traffic Prediction Long short-term memory

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.448545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e58e7e67-466d-4582-abe8-7aeacc2aa7e2 · outbound

This paper cites Attention is all you need.

Virtual Nodes Improve Long-term Traffic Prediction Attention is all you need

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.454472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96e0ed75-e28f-4dee-83f1-93555fc69658 · outbound

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

Virtual Nodes Improve Long-term Traffic Prediction Diffusion convolutional recurrent neural network: Data-driven traffic forecasting

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.085380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1f30bb9e-e159-49c4-b162-f5d9f2767ce9 · outbound

This paper cites Predicting station-level short-term passenger flow in a citywide metro network using spatiotemporal graph convolutional neural networks.

Virtual Nodes Improve Long-term Traffic Prediction Predicting station-level short-term passenger flow in a citywide metro network using spatiotemporal graph convolutional neural networks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.067518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9e1c23a4-155d-4470-9978-1ebdb4a34ba0 · outbound

This paper cites Dynamic and multi-faceted spatio-temporal deep learning for traffic speed forecasting.

Virtual Nodes Improve Long-term Traffic Prediction Dynamic and multi-faceted spatio-temporal deep learning for traffic speed forecasting

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.048434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4c4201c9-f3a5-47e3-8f55-6f75489c4294 · outbound

This paper cites Stgat: Spatial-temporal graph attention networks for traffic flow forecasting.

Virtual Nodes Improve Long-term Traffic Prediction Stgat: Spatial-temporal graph attention networks for traffic flow forecasting

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.474454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60cfb17e-062c-496e-8417-f046df7d0f91 · outbound

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

Virtual Nodes Improve Long-term Traffic Prediction Decoupled dynamic spatial-temporal graph neural network for traffic forecasting

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.017999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c8fda691-0b59-4ef0-8699-473bcef67394 · outbound

This paper cites Learning phrase representations using rnn encoder--decoder for statistical machine translation.

Virtual Nodes Improve Long-term Traffic Prediction Learning phrase representations using rnn encoder--decoder for statistical machine translation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:15.000847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ee07b1fd-60a9-4aae-b7dc-d8a9f8ea45a3 · outbound

This paper cites Temporal convolutional networks for action segmentation and detection.

Virtual Nodes Improve Long-term Traffic Prediction Temporal convolutional networks for action segmentation and detection

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:14.982434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation af1bf1a0-84ea-4213-9ab5-a3bc7b98edb4 · outbound

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

Virtual Nodes Improve Long-term Traffic Prediction Deep multi-view spatial-temporal network for taxi demand prediction

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:14.963321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 806d830f-e779-42c2-9513-f6939e217245 · outbound

This paper cites Revisiting spatial-temporal similarity: A deep learning framework for traffic prediction.

Virtual Nodes Improve Long-term Traffic Prediction Revisiting spatial-temporal similarity: A deep learning framework for traffic prediction

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:14.940993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 860f8d64-a848-498d-b9fe-82504b4ebc46 · outbound

This paper cites Graph wavenet for deep spatial-temporal graph modeling.

Virtual Nodes Improve Long-term Traffic Prediction Graph wavenet for deep spatial-temporal graph modeling

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:14.920767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c90e71ba-f914-42e9-ba87-4dc03053d3e0 · outbound

This paper cites Dynamic graph convolutional recurrent network for traffic prediction: Benchmark and solution.

Virtual Nodes Improve Long-term Traffic Prediction Dynamic graph convolutional recurrent network for traffic prediction: Benchmark and solution

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:14.903425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4e30638b-b441-486c-af7a-5fcd6b030d5c · outbound

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

Virtual Nodes Improve Long-term Traffic Prediction Gman: A graph multi-attention network for traffic prediction

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:14.885369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 19e8f914-c2c3-40f7-9c3a-7ce7f9684a82 · outbound

This paper cites Structure-aware transformer for graph representation learning.

Virtual Nodes Improve Long-term Traffic Prediction Structure-aware transformer for graph representation learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:14.868357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 00d2dded-6917-4682-81b2-6b161b1d398e · outbound

This paper cites Pure transformers are powerful graph learners.

Virtual Nodes Improve Long-term Traffic Prediction Pure transformers are powerful graph learners

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.524683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0c22322-ff11-4158-9671-8e60eb7fc0ec · outbound

This paper cites Long range graph benchmark.

Virtual Nodes Improve Long-term Traffic Prediction Long range graph benchmark

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.529294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b973c6db-6ab8-4bba-a830-3a4ff4ca0545 · outbound

This paper cites Representing long-range context for graph neural networks with global attention.

Virtual Nodes Improve Long-term Traffic Prediction Representing long-range context for graph neural networks with global attention

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:14.829382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2162d20d-e703-4f95-829d-082a521674d5 · outbound

This paper cites Revisiting virtual nodes in graph neural networks for link prediction, 2022.

Virtual Nodes Improve Long-term Traffic Prediction Revisiting virtual nodes in graph neural networks for link prediction, 2022

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:14.811319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 54154535-adb7-4aa4-a875-e5f86be89a89 · outbound

This paper cites Probabilistic Graph Rewiring via Virtual Nodes.

Virtual Nodes Improve Long-term Traffic Prediction Probabilistic Graph Rewiring via Virtual Nodes

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-08-10T19:27:14.688877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 34160257-6f88-45c0-aff6-060b34c61c03 · outbound

This paper cites Rewiring with Positional Encodings for Graph Neural Networks.

Virtual Nodes Improve Long-term Traffic Prediction Rewiring with Positional Encodings for Graph Neural Networks

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.548019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69c80129-2f83-4408-9c18-904356506e28 · outbound

This paper cites Probabilistically Rewired Message-Passing Neural Networks.

Virtual Nodes Improve Long-term Traffic Prediction Probabilistically Rewired Message-Passing Neural Networks

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.552994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1757fef3-f6f9-4ebc-b9a6-b5393c8a70ff · outbound

This paper cites Timegnn: Temporal dynamic graph learning for time series forecasting.

Virtual Nodes Improve Long-term Traffic Prediction Timegnn: Temporal dynamic graph learning for time series forecasting

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:14.791374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c3370ae3-59fc-4203-846f-d86377f8bd07 · outbound

This paper cites Balanced Graph Structure Learning for Multivariate Time Series Forecasting.

Virtual Nodes Improve Long-term Traffic Prediction Balanced Graph Structure Learning for Multivariate Time Series Forecasting

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-10T19:27:14.627661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation debb7e39-367f-46be-86b9-4afb3e1a8aa4 · outbound

This paper cites Connecting the dots: Multivariate time series forecasting with graph neural networks.

Virtual Nodes Improve Long-term Traffic Prediction Connecting the dots: Multivariate time series forecasting with graph neural networks

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.567919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83075d91-ba52-411c-ba17-a1e025638908 · outbound

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

Virtual Nodes Improve Long-term Traffic Prediction Largest: A benchmark dataset for large-scale traffic forecasting

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:14.572357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 569aaa56-d9d6-408f-b8d2-0c3f7dd2d8d7 · outbound

This paper cites The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains.

Virtual Nodes Improve Long-term Traffic Prediction The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:27:14.750531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

Observation 003d21bd-5c3a-499b-8a38-cac02b5deff3 · inbound

Built Environment Reasoning from Remote Sensing Imagery Using Large Vision--Language Models cites this paper.

Built Environment Reasoning from Remote Sensing Imagery Using Large Vision--Language Models Virtual Nodes Improve Long-term Traffic Prediction

Reference 231

Resolution: verified exact; arxiv_id, observed 2026-05-12T01:11:13.412833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.