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Paper Citation Record · LEDGER

A Road-Conditioned Traffic Movie Prediction Network with Spatiotemporal and Structure-Consistent Learning

As of 12 August 2026, this Paper Citation Record lists 4 of 4 outbound references and 0 inbound Pith citation observations for arXiv:2605.27884.

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

pith.paper-citation-record.v1
2605.27884 v1

Coverage vector

measured 4 of 4 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T13:55:31.399633Z

measured 4 of 4 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 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

4 of 4 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b3f7b413-8650-4c0c-8961-3a6dc30a3c91 · outbound

This paper cites SwinUNet3D -- A Hierarchical Architecture for Deep Traffic Prediction using Shifted Window Transformers.

A Road-Conditioned Traffic Movie Prediction Network with Spatiotemporal and Structure-Consistent Learning SwinUNet3D -- A Hierarchical Architecture for Deep Traffic Prediction using Shifted Window Transformers

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:03:29.697223Z

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.

source=pdf_text observed=2026-06-29T13:55:31.399633Z digest=sha256:6406e7451a7d68840d674a18b8459284faec37cb909eb502fa5be181b7ae6e8e

Observation 7f769cee-aa12-4254-8560-fe8442d1ea96 · outbound

This paper cites Integrating Travel Behavior Forecasting and Generative Modeling for Predicting Future Urban Mobility and Spatial Transformations.

A Road-Conditioned Traffic Movie Prediction Network with Spatiotemporal and Structure-Consistent Learning Integrating Travel Behavior Forecasting and Generative Modeling for Predicting Future Urban Mobility and Spatial Transformations

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:03:29.703214Z

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.

source=pdf_text observed=2026-06-29T13:55:31.399633Z digest=sha256:b5ab7cdba14c81ef887c7aa0ab6f67397f08becfd7414bc9b467046ca9910ba6

Observation 2c12e0eb-d0e3-4d1a-bc13-c033888931e3 · outbound

This paper cites Solving Traffic4Cast Competition with U-Net and Temporal Domain Adaptation.

A Road-Conditioned Traffic Movie Prediction Network with Spatiotemporal and Structure-Consistent Learning Solving Traffic4Cast Competition with U-Net and Temporal Domain Adaptation

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:03:29.705445Z

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.

source=pdf_text observed=2026-06-29T13:55:31.399633Z digest=sha256:3f90683be68b28f82c3663b22c2cb6aebedddf915738243367d5fed9f67dea62

Observation ca8a9135-2b1f-4343-8385-834d54d03662 · outbound

This paper cites Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting.

A Road-Conditioned Traffic Movie Prediction Network with Spatiotemporal and Structure-Consistent Learning Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting

Reference 4

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T14:03:29.702686Z

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.

source=pdf_text observed=2026-06-29T13:55:31.399633Z digest=sha256:17da715b92b00280fa745b71398325ee40ac66e4e508ae8f2fb16cb8ae328e5c

Pith citing papers

No inbound Pith citation observations are available.