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Paper Citation Record · LEDGER

Is Mamba Effective for Time Series Forecasting?

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2403.11144.

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

pith.paper-citation-record.v1
2403.11144 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:02:41.642908Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T04:22:31.029374Z

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 95ae66ef-9070-4a3f-9737-4c7561f22b40 · inbound

Recency Biased Causal Attention for Time-series Forecasting cites this paper.

Recency Biased Causal Attention for Time-series Forecasting Is Mamba Effective for Time Series Forecasting?

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:22:31.032388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T04:21:47.202310Z digest=sha256:8ffdcce7ff46e69c86a62eb6df8b263097fddfb5905e56d2d35c93cb90564bcd

Observation c07f22d5-ab8e-4475-83cd-47cd9f211e4f · inbound

KARMA: A Multilevel Decomposition Hybrid Mamba Framework for Multivariate Long-Term Time Series Forecasting cites this paper.

KARMA: A Multilevel Decomposition Hybrid Mamba Framework for Multivariate Long-Term Time Series Forecasting Is Mamba Effective for Time Series Forecasting?

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T05:02:41.642908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:02:41.642908Z digest=sha256:e3e31dac3fb48f92cc179b4e1bd435270530f182bc3a4e5816350ed88373a1f8

Observation 912c02f0-3d45-4b97-8df6-b49953218111 · inbound

Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions cites this paper.

Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions Is Mamba Effective for Time Series Forecasting?

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-06T21:27:49.079891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:27:49.079891Z digest=sha256:463d00fb15cea7794ae7e8d02e9ed7695ed7c464fdfc326711ad90255484a025

Observation e4efa527-9362-4fc1-aae0-b94801d41b05 · inbound

MCST-Mamba: Multivariate Mamba-Based Model for Traffic Prediction cites this paper.

MCST-Mamba: Multivariate Mamba-Based Model for Traffic Prediction Is Mamba Effective for Time Series Forecasting?

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T20:03:43.336851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:03:43.336851Z digest=sha256:a985e000c91e263805038e84a3ac3074a3cf65fe78eb472559d8555fe4f835a5

Observation cd1bdf6f-f7fc-40cf-bd53-0dc714dd512d · inbound

Quantum-Optimized Selective State Space Model for Efficient Time Series Prediction cites this paper.

Quantum-Optimized Selective State Space Model for Efficient Time Series Prediction Is Mamba Effective for Time Series Forecasting?

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T13:54:04.287140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:54:04.287140Z digest=sha256:58332e701c0aa7c76f5f310200368ce2771a3955e0b8cf8bceb8784cab46dfc7

Observation ad538ce0-f2ef-43bd-b995-e82beb20ecbe · inbound

UniMamba: A Unified Spatial-Temporal Modeling Framework with State-Space and Attention Integration cites this paper.

UniMamba: A Unified Spatial-Temporal Modeling Framework with State-Space and Attention Integration Is Mamba Effective for Time Series Forecasting?

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-15T14:51:08.488337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T14:50:08.468635Z digest=sha256:c480b2e1d6ee1bc4ff03427a8fd6f2f944e9be8d34ec1e2a9eb0bd2a3ed961f6