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Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 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 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T08:34:26.300971Z

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

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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 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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T02:49:40.277048Z digest=sha256:cb33c1d0137a3699d246d6116911947ab0922e63760d54e72d93ec51f509498d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T13:03:25.032299Z digest=sha256:ebb23890dc92217d2b17a04aa20f1c615528bce7a18575205d853cc19b89db6a

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.

source=pdf_text observed=2026-08-03T08:34:26.300971Z digest=sha256:3abfca482cefdfe08bb81aaf9d4bc5be9cb298a04b2e6119faacbb6e016a62a5

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T09:03:49.988075Z digest=sha256:ff78f59212e4df83ce69f44f5f361eda21405aa56574c7482bd552e70869e1a9

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.

source=pdf_text observed=2026-08-03T02:44:15.818976Z digest=sha256:5ee3b4caaf6162984219e15efb8bda618061e49da562ccab90d41130cf5c1687

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-12T02:36:18.686443Z digest=sha256:379ff87417c2f4d9424f0f036d12e5f3a0264f5ca18d808ac8294165ba86ad7a

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T01:54:32.493922Z digest=sha256:92bb2bb32d28803f51486e4c3e01f8f51aad8dfdbc84076f1b6748e496b70d64

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-20T12:25:42.754858Z digest=sha256:8fdaa780f0ead6a0b46f89d4dfebbb61aae90f2c9a1f61f17d967a5ed993b462

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T11:17:45.288201Z digest=sha256:ee70fa3d59c23230a83ed78972a9e34caae8e2031c9f61ff5cc3435e8395972b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T13:41:52.295889Z digest=sha256:8aafd541b09bcf9f13406522866ea01f4f83b42e763d3ea1648b00feb798a0be

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.

source=arxiv_source observed=2026-07-31T19:49:57.532870Z digest=sha256:9050b5c9a67d12c5c91679040b30491182eb1a46f22321338f89dfe0a8441a33