Paper Citation Record · LEDGER

TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2410.04442.

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

pith.paper-citation-record.v1
2410.04442 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:28:50.161399Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:47:37.819628Z

Reference resolution

0 of 0 outbound references displayed

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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 e3874e22-3ef4-4a3e-b356-9c742f0cd201 · inbound

DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting cites this paper.

DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T15:37:04.279656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf3844c7-68b5-42c4-9b70-8b4db9deadb4 · inbound

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis cites this paper.

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T17:16:27.395821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef91e8c8-4126-4549-bb40-75eea288edd9 · inbound

TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting cites this paper.

TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-10T16:35:14.405028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29b1647a-dae7-401e-acf8-9f1ebd83d742 · inbound

FinMamba: Market-Aware Graph Enhanced Multi-Level Mamba for Stock Movement Prediction cites this paper.

FinMamba: Market-Aware Graph Enhanced Multi-Level Mamba for Stock Movement Prediction TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T14:39:27.265809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d225f3f5-9a7e-4a8f-afd2-ab7c43be00d5 · inbound

FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting cites this paper.

FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:52:26.643124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 425ba032-a52e-4db9-b573-b3a6182f2416 · inbound

Temporal Query Network for Efficient Multivariate Time Series Forecasting cites this paper.

Temporal Query Network for Efficient Multivariate Time Series Forecasting TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:50.161399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 463a510d-ddf1-430e-b253-742b07c6b2fe · inbound

Stationarity Exploration for Multivariate Time Series Forecasting cites this paper.

Stationarity Exploration for Multivariate Time Series Forecasting TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-15T17:37:26.363939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 959ec942-8d42-449d-b848-c4cb5ed5b721 · inbound

ReNF: Rethinking the Design of Neural Long-Term Time Series Forecasters cites this paper.

ReNF: Rethinking the Design of Neural Long-Term Time Series Forecasters TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:06:23.916116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f198b80e-47c7-46c9-a980-583c9da9cb36 · inbound

Dual-Prototype Disentanglement: A Context-Aware Enhancement Framework for Time Series Forecasting cites this paper.

Dual-Prototype Disentanglement: A Context-Aware Enhancement Framework for Time Series Forecasting TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T08:34:26.300971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08cdc771-31a7-44d1-80f5-2314f96374d8 · inbound

From Observations to States: Latent Time Series Forecasting cites this paper.

From Observations to States: Latent Time Series Forecasting TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-16T09:07:39.256936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f7ba5198-8fde-48bc-9bc3-be4e010257c2 · inbound

Forecasting as Rendering: A 2D Gaussian Splatting Framework for Time Series Forecasting cites this paper.

Forecasting as Rendering: A 2D Gaussian Splatting Framework for Time Series Forecasting TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:15.818976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c541bf40-b984-4545-81bb-23197a369bfc · inbound

What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies cites this paper.

What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 106

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:31:26.934913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ec244ec0-44b9-45c6-8a1a-af99dcb81e23 · inbound

SeesawNet: Towards Non-stationary Time Series Forecasting with Balanced Modeling of Common and Specific Dependencies cites this paper.

SeesawNet: Towards Non-stationary Time Series Forecasting with Balanced Modeling of Common and Specific Dependencies TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-15T01:58:29.215951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 03844eae-7e6d-4689-aa4c-63d6fad5b4ca · inbound

L-Drive: Beyond a Single Mapping-Latent Context Drives Time Series Forecasting cites this paper.

L-Drive: Beyond a Single Mapping-Latent Context Drives Time Series Forecasting TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:28:16.788685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 56c7cf21-b9dc-40cb-8fc6-f0d3d3fe2a5f · inbound

Stationarity-Aware Retrieval-Augmented Time Series Forecasting cites this paper.

Stationarity-Aware Retrieval-Augmented Time Series Forecasting TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:06:26.494582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 96997778-6d03-400c-921a-2450d2d94176 · inbound

One Step Closer to Ground Truth: A Multi-Scale Residual-Aware Representation Learning Pipeline for Predicting Time Series Data cites this paper.

One Step Closer to Ground Truth: A Multi-Scale Residual-Aware Representation Learning Pipeline for Predicting Time Series Data TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:47:37.820862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 889f9b5e-bc22-4169-b5f4-902d297c58b7 · inbound

Enhancing Irregular Time Series Forecasting with Continuous-Time Modeling Framework cites this paper.

Enhancing Irregular Time Series Forecasting with Continuous-Time Modeling Framework TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Reference 238

Resolution: unresolved; no resolver link, observed 2026-07-31T19:49:57.532870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.