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Paper Citation Record · LEDGER

TSLANet: Rethinking Transformers for Time Series Representation Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2404.08472.

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

pith.paper-citation-record.v1
2404.08472 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:35:25.899010Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:19:50.473055Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • 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 9f08df83-03ca-458e-80a3-d3d6aa5b95bd · inbound

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting cites this paper.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting TSLANet: Rethinking Transformers for Time Series Representation Learning

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T16:35:25.899010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:35:25.899010Z digest=sha256:ee029007a3521b61686f562a77e7bc27576f0645f34247786eb350a5f0c22b61

Observation 7bdfdd6f-659f-4fd0-8c23-a63cc905ba69 · inbound

Fed-REACT: Federated Representation Learning for Heterogeneous and Evolving Data cites this paper.

Fed-REACT: Federated Representation Learning for Heterogeneous and Evolving Data TSLANet: Rethinking Transformers for Time Series Representation Learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-04T22:44:39.641708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T22:44:39.641708Z digest=sha256:0f28573ab234206f8ff4751b2482021ccbb6d640b4975946c9eb08d48aa29c4b

Observation f260c8e7-e2a2-4185-88f1-2ce5ab177fb7 · inbound

Characteristic Root Analysis and Regularization for Linear Time Series Forecasting cites this paper.

Characteristic Root Analysis and Regularization for Linear Time Series Forecasting TSLANet: Rethinking Transformers for Time Series Representation Learning

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-18T12:51:23.423720Z

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=arxiv_source observed=2026-05-18T12:49:02.077485Z digest=sha256:dbdcd451de4d38128233a02026843da744d5954899a2b7366a3660e5641f64a2

Observation c52a2bd8-4626-4761-ada1-b129a40d2a4f · inbound

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

From Observations to States: Latent Time Series Forecasting TSLANet: Rethinking Transformers for Time Series Representation Learning

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-16T09:07:39.278025Z

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=2026-05-16T09:03:49.988075Z digest=sha256:5c3d838ac922ec6ce1c57d6b374b3db4650188faf1098685be56c7e82a7d8bb5

Observation ffc35c97-eef1-4bf3-9ffd-2ab50279ec2e · inbound

Modular Retrieval-Augmented Generalization for Human Action Recognition cites this paper.

Modular Retrieval-Augmented Generalization for Human Action Recognition TSLANet: Rethinking Transformers for Time Series Representation Learning

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:36:25.818113Z

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=2026-05-12T00:56:24.885299Z digest=sha256:f2fa5e8d4aada380900a282038cd9eb6852151199841f9769c2e20542614ae2c

Observation 341e3c10-5fd8-4ad8-a45f-be9295ddc69f · inbound

Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series cites this paper.

Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series TSLANet: Rethinking Transformers for Time Series Representation Learning

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-22T08:26:16.635124Z

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=2026-05-22T08:25:32.231942Z digest=sha256:0e491c5cf23cdb7f0f750d9e0722ba35d85ba0bc6ba7b61c9a7b89a135e283ad

Observation ce0dc290-ccf5-4672-bf0c-429cfc963bfc · inbound

PMDformer: Patch-Mean Decoupling Information Transformer for Long-term Forecasting cites this paper.

PMDformer: Patch-Mean Decoupling Information Transformer for Long-term Forecasting TSLANet: Rethinking Transformers for Time Series Representation Learning

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:19:50.474622Z

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=2026-06-26T05:22:10.800685Z digest=sha256:570807dcc9ca4bf1a3fb64da1eed9327a35bfdf5c17df8996dbfa2023c392223

Observation 0b0a2046-5795-4925-abe3-d3a199cd5bb3 · inbound

See the Emotion: A Facial Emoji Proxy Modeling for EEG Emotion Recognition cites this paper.

See the Emotion: A Facial Emoji Proxy Modeling for EEG Emotion Recognition TSLANet: Rethinking Transformers for Time Series Representation Learning

Reference 2

Resolution
unresolved
no resolver link, observed 2026-07-12T06:11:08.642700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T06:11:08.642700Z digest=sha256:ac8ffab14686b4363f3c04bf80609a3840cc81836ac13aa0d25098185fb98ea5