Paper Citation Record · LEDGER

SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2405.00946.

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

pith.paper-citation-record.v1
2405.00946 v2

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 2026-08-08T00:50:44.713194Z

measured 0 of 1 external citation measurements

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

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
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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 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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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.