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Paper Citation Record · LEDGER

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting

As of 8 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2506.00798.

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

pith.paper-citation-record.v1
2506.00798 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:04:15.548185Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

31 of 31 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3f6f3682-e036-4557-87b5-624ab6a2b793 · outbound

This paper cites Uci machine learning repository,.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Uci machine learning repository,

Reference 1

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Observation 61ce2b3c-1aa4-419d-a12a-fe2e7709b82d · outbound

This paper cites an unresolved cited work.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Unresolved cited work

Reference 3

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Observation c31600d3-a44f-4c77-85d2-d7a175b53c2a · outbound

This paper cites Spectral temporal graph neural network for multivariate time-series forecast- ing.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Spectral temporal graph neural network for multivariate time-series forecast- ing

Reference 4

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Observation 6bad262d-697a-4f8a-a097-5fede56ff027 · outbound

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

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Convolutional neural networks on graphs with fast localized spectral filtering

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation b00dcf25-e7a7-4e8a-81cc-c7b938481856 · outbound

This paper cites Modeling long-and short-term temporal patterns with deep neural networks.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Modeling long-and short-term temporal patterns with deep neural networks

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9429175d-fd5a-438b-ad6a-d518115f7bfe · outbound

This paper cites Multichannel spatial– temporal graph convolution network based on spectrum decomposition for traffic prediction.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Multichannel spatial– temporal graph convolution network based on spectrum decomposition for traffic prediction

Reference 13

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Source-reported events for the cited work

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Observation a5a1e9c7-a8cf-4085-a3e8-dc283cfe86da · outbound

This paper cites CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns

Reference 14

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Source-reported events for the cited work

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Observation 14b84d8d-bb4b-45d4-b4ba-14c9f12a6064 · outbound

This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 15

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Source-reported events for the cited work

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Observation 8e522a90-b891-4d5c-8188-7f0f3f3b3430 · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 16

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Source-reported events for the cited work

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Observation c8787c0a-1fb7-4982-bdab-7410ea6c531f · outbound

This paper cites Fred- former: Frequency debiased transformer for time series forecasting.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Fred- former: Frequency debiased transformer for time series forecasting

Reference 18

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Source-reported events for the cited work

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Observation e93677fb-9e3a-419e-9399-22fd5814785a · outbound

This paper cites Saurous, and Matthew Hoffman.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Saurous, and Matthew Hoffman

Reference 19

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Source-reported events for the cited work

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Observation 34b6abab-8a75-41d8-9915-c0f19b5dfd4e · outbound

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

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Spatial-temporal synchronous graph convolutional networks: A new framework for spatial- temporal network data forecasting

Reference 20

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Source-reported events for the cited work

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Observation a26b6260-c22f-4f57-b970-33e053e4b37a · outbound

This paper cites Modwavemlp: Mlp-based mode decomposition and wavelet denoising model to defeat complex structures in traffic forecasting.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Modwavemlp: Mlp-based mode decomposition and wavelet denoising model to defeat complex structures in traffic forecasting

Reference 21

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Observation 66a246a9-0a49-470b-99c8-8ba1ce372741 · outbound

This paper cites TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 22

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Source-reported events for the cited work

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Observation c07f34d3-fa70-4227-af1c-70b543a73c5b · outbound

This paper cites TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables

Reference 23

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Source-reported events for the cited work

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Observation 60124242-4ea5-4c3e-95ed-479064cb99ad · outbound

This paper cites Autoformer: Decomposition transform- ers with auto-correlation for long-term series forecast- ing.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Autoformer: Decomposition transform- ers with auto-correlation for long-term series forecast- ing

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e56c3a01-2cf7-41de-b0f8-3e8555007c47 · outbound

This paper cites TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis

Reference 25

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Source-reported events for the cited work

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Observation 20454fab-5548-4295-859d-27ce6b24866e · outbound

This paper cites FITS: Modeling Time Series with $10k$ Parameters.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting FITS: Modeling Time Series with $10k$ Parameters

Reference 26

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Observation 11090462-d7b9-4e3d-a7f5-35b663597dba · outbound

This paper cites Fedgtp: Exploiting inter-client spatial dependency in fed- erated graph-based traffic prediction.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Fedgtp: Exploiting inter-client spatial dependency in fed- erated graph-based traffic prediction

Reference 27

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verified fuzzy
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Source-reported events for the cited work

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Observation d8533944-2866-4ac6-b666-142f033a7361 · outbound

This paper cites Geoexplainer: Interpreting graph convo- lutional networks with geometric masking.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Geoexplainer: Interpreting graph convo- lutional networks with geometric masking

Reference 28

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Source-reported events for the cited work

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Observation 6f72e7d6-3600-4225-97e7-58be739df1c6 · outbound

This paper cites Multi- resolution time-series transformer for long-term forecast- ing.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Multi- resolution time-series transformer for long-term forecast- ing

Reference 29

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Source-reported events for the cited work

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Observation 2ba3cf5f-63cc-4a11-8c16-259de78956da · outbound

This paper cites Multi-resolution patch-based fourier graph spectral network for spatiotemporal time series forecasting.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Multi-resolution patch-based fourier graph spectral network for spatiotemporal time series forecasting

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation b92c8a33-8cc1-4415-b7ac-10dcee3175c9 · outbound

This paper cites Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs

Reference 2007

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Observation dce2d423-ece5-4fa4-95a8-91dd521be178 · outbound

This paper cites Istgcn: Inte- grated spatio-temporal modeling for traffic prediction us- ing traffic graph convolution network.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Istgcn: Inte- grated spatio-temporal modeling for traffic prediction us- ing traffic graph convolution network

Reference 2016

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Source-reported events for the cited work

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Observation 60a44f9e-9964-4899-a87e-c1c417264352 · outbound

This paper cites Llgformer: Learnable long-range graph transformer for traffic flow prediction.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Llgformer: Learnable long-range graph transformer for traffic flow prediction

Reference 2018

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6da568b2-ccd6-4911-ace0-21ab98891785 · outbound

This paper cites Ad- dressing spatial-temporal heterogeneity: General mixed time series analysis via latent continuity recovery and alignment.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Ad- dressing spatial-temporal heterogeneity: General mixed time series analysis via latent continuity recovery and alignment

Reference 2020

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Source-reported events for the cited work

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Observation e1a9e310-fbe2-4e07-8cf2-eb69d2268461 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Semi-Supervised Classification with Graph Convolutional Networks

Reference 2021

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Source-reported events for the cited work

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Observation 31743f99-b7d8-4cae-9fe0-c5c3cfcdc946 · outbound

This paper cites Ma-gcn: A memory augmented graph convolutional net- work for traffic prediction.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Ma-gcn: A memory augmented graph convolutional net- work for traffic prediction

Reference 2022

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verified fuzzy
raw_fallback, observed 2026-08-07T12:04:18.649143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation ca6323d4-4d6b-4486-91d3-493a8c4e05b9 · outbound

This paper cites Orthogonal weight normalization: Solution to optimization over mul- tiple dependent stiefel manifolds in deep neural networks.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Orthogonal weight normalization: Solution to optimization over mul- tiple dependent stiefel manifolds in deep neural networks

Reference 2023

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verified fuzzy
raw_fallback, observed 2026-08-07T12:04:20.153434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e5a4e3f3-4506-4827-9b15-ceeb8d4575fa · outbound

This paper cites Multi-head multi-order graph attention networks.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Multi-head multi-order graph attention networks

Reference 2024

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verified fuzzy
raw_fallback, observed 2026-08-07T12:04:21.125250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation d3dd16d3-c9df-4585-8bcb-6774ec3b9254 · outbound

This paper cites Re- versible instance normalization for accurate time-series forecasting against distribution shift.

A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting Re- versible instance normalization for accurate time-series forecasting against distribution shift

Reference 2025

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verified fuzzy
raw_fallback, observed 2026-08-07T12:04:19.721011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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