Paper Citation Record · LEDGER

Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:1801.02143.

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

pith.paper-citation-record.v1
1801.02143 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:51:45.135600Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T03:45:21.657013Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2f282bc6-6801-4c30-b940-6a56c73b8d93 · inbound

Bi-Directional ConvLSTM U-Net with Densley Connected Convolutions cites this paper.

Bi-Directional ConvLSTM U-Net with Densley Connected Convolutions Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-14T06:06:37.130592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f12013d1-a4d8-4047-a156-04463567f819 · inbound

MPBD-LSTM: A Predictive Model for Colorectal Liver Metastases Using Time Series Multi-phase Contrast-Enhanced CT Scans cites this paper.

MPBD-LSTM: A Predictive Model for Colorectal Liver Metastases Using Time Series Multi-phase Contrast-Enhanced CT Scans Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T00:04:35.782957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dfd20c8-981a-4b2e-8dcd-f5c7b5eae0bb · inbound

Wind Speed Forecasting Based on Data Decomposition and Deep Learning Models: A Case Study of a Wind Farm in Saudi Arabia cites this paper.

Wind Speed Forecasting Based on Data Decomposition and Deep Learning Models: A Case Study of a Wind Farm in Saudi Arabia Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-11T13:16:49.211952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4332c275-eb16-4f83-891e-587408c96d78 · inbound

Social media polarization during conflict: Insights from an ideological stance dataset on Israel-Palestine Reddit comments cites this paper.

Social media polarization during conflict: Insights from an ideological stance dataset on Israel-Palestine Reddit comments Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:45:21.660340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b8df766e-c2fe-4ede-9d26-b15da12a7c47 · inbound

Investigating Compositional Reasoning in Time Series Foundation Models cites this paper.

Investigating Compositional Reasoning in Time Series Foundation Models Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T17:06:02.985535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c10e31a4-584e-47c6-9e1b-e5d94bc251ce · inbound

A Double-Norm Aggregated Tensor Latent Factorization Model for Temporal-Aware Traffic Speed Imputation cites this paper.

A Double-Norm Aggregated Tensor Latent Factorization Model for Temporal-Aware Traffic Speed Imputation Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-16T10:51:45.135600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a684307-bace-4fcc-a3d4-ced32194a74b · inbound

Forecasting at Full Spectrum: Holistic Multi-Granular Traffic Modeling under High-Throughput Inference Regimes cites this paper.

Forecasting at Full Spectrum: Holistic Multi-Granular Traffic Modeling under High-Throughput Inference Regimes Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T04:27:17.485159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e4d4b4c-41b6-4058-8656-f6aea7191fa1 · inbound

Kernel Dynamic Mode Decomposition For Sparse Reconstruction of Closable Koopman Operators cites this paper.

Kernel Dynamic Mode Decomposition For Sparse Reconstruction of Closable Koopman Operators Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T22:38:36.933105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 123de6ea-1f1f-46a3-882b-dd622cc9c8fd · inbound

Programmable-Room: Interactive Textured 3D Room Meshes Generation Empowered by Large Language Models cites this paper.

Programmable-Room: Interactive Textured 3D Room Meshes Generation Empowered by Large Language Models Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T19:06:31.051336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 785396e2-6f62-437e-a4bb-e3c0de88143f · inbound

PHASE: Passive Human Activity Simulation Evaluation cites this paper.

PHASE: Passive Human Activity Simulation Evaluation Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T16:27:12.593409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0ec671d-e25d-4f90-b41c-912806629ddc · inbound

Graph Coloring for Multi-Task Learning cites this paper.

Graph Coloring for Multi-Task Learning Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:32.835363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 744022e4-2fd9-4784-85b5-30106a02b0d7 · inbound

MICA: Multivariate Infini Compressive Attention for Time Series Forecasting cites this paper.

MICA: Multivariate Infini Compressive Attention for Time Series Forecasting Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:55:52.208039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4dfd3a67-2061-44ea-98ea-881b75c7ac34 · inbound

MICA: Multivariate Infini Compressive Attention for Time Series Forecasting cites this paper.

MICA: Multivariate Infini Compressive Attention for Time Series Forecasting Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:11:15.640771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.