Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2405.00946.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T00:42:13.040800Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T13:19:51.303322Z
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 003f7941-d969-451a-a39d-068e0d5de7e4 · inbound
Revisiting PCA for time series reduction in temporal dimension cites this paper.
Revisiting PCA for time series reduction in temporal dimension SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T00:42:13.040800Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4ec68a00-01c7-461f-985d-5ac54b0f6817 · inbound
Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences cites this paper.
Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:12:06.428920Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bb46e58a-f64a-42b0-a7f6-24f417c464ad · inbound
Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting cites this paper.
Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:46:00.463555Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 346a2f86-9ecb-403a-beea-121cf1194ab3 · inbound
CrossLinear: Plug-and-Play Cross-Correlation Embedding for Time Series Forecasting with Exogenous Variables cites this paper.
CrossLinear: Plug-and-Play Cross-Correlation Embedding for Time Series Forecasting with Exogenous Variables SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:57:49.163511Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 83f1011c-0db9-46e0-987e-e5f54baabb9c · inbound
DisMS-TS: Eliminating Redundant Multi-Scale Features for Time Series Classification cites this paper.
DisMS-TS: Eliminating Redundant Multi-Scale Features for Time Series Classification SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:52:20.725772Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f69a353f-6f89-4899-8a39-ac66b9b3cec7 · inbound
Fremer: Lightweight and Effective Frequency Transformer for Workload Forecasting in Cloud Services cites this paper.
Fremer: Lightweight and Effective Frequency Transformer for Workload Forecasting in Cloud Services SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:41:25.776567Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c9511ce-93cd-4a06-b560-049b29965b7c · inbound
Super-Linear: A Lightweight Pretrained Mixture of Linear Experts for Time Series Forecasting cites this paper.
Super-Linear: A Lightweight Pretrained Mixture of Linear Experts for Time Series Forecasting SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T08:25:34.186114Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9e858d2f-a8e9-45fa-91cc-f4ff694cd62c · inbound
Characteristic Root Analysis and Regularization for Linear Time Series Forecasting cites this paper.
Characteristic Root Analysis and Regularization for Linear Time Series Forecasting SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T12:51:23.408170Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation cd0e81d9-fa43-4c2d-980b-219f78dc7c6a · inbound
Parametric Prior Mapping Framework for Non-stationary Probabilistic Time Series Forecasting cites this paper.
Parametric Prior Mapping Framework for Non-stationary Probabilistic Time Series Forecasting SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-25T05:10:22.018038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 31ea82f4-1fc2-443a-b2de-3464471cd2ef · 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 SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T04:47:37.821253Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4a31e250-6073-40ac-8f66-2c0991d46709 · inbound
How Good Can Linear Models Be for Time-Series Forecasting? cites this paper.
How Good Can Linear Models Be for Time-Series Forecasting? SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T13:19:51.304767Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ad40b982-a778-440c-ae89-8a18236e0df6 · inbound
How Good Can Linear Models Be for Time-Series Forecasting? cites this paper.
How Good Can Linear Models Be for Time-Series Forecasting? SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T09:34:34.433513Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation aee802ad-db6c-421b-8edb-8f15b9901193 · inbound
CAMP: A Cycle-Aware Multi-Scale Patch Mixer for Time Series Forecasting cites this paper.
CAMP: A Cycle-Aware Multi-Scale Patch Mixer for Time Series Forecasting SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T00:50:44.713194Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.