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Paper Citation Record · LEDGER

SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2308.11200.

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

pith.paper-citation-record.v1
2308.11200 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:00:11.184781Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T22:24:00.013053Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation cb822c54-bf28-43aa-aed2-7bf9db2b5e90 · inbound

PIAD-SRNN: Physics-Informed Adaptive Decomposition in State-Space RNN cites this paper.

PIAD-SRNN: Physics-Informed Adaptive Decomposition in State-Space RNN SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 2000

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no resolver link, observed 2026-08-12T04:51:40.668388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:51:40.668388Z digest=sha256:3757e380a6bf91f18f298753d2c44d212ccfc7f28fd01f83268a2156bb405453

Observation 41d7f135-d2fd-4c0b-a571-9c6b50e2c411 · inbound

WinTSR: A Windowed Temporal Saliency Rescaling Method for Interpreting Time Series Deep Learning Models cites this paper.

WinTSR: A Windowed Temporal Saliency Rescaling Method for Interpreting Time Series Deep Learning Models SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 2021

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no resolver link, observed 2026-08-11T21:35:48.776965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:35:48.776965Z digest=sha256:e1393c13032e78ac88cf50101000c86c6e40c30bce6b7dc1205e7eaa03baf67d

Observation 20dc6c9c-ec90-4b42-acc0-3d672ddc5fa9 · inbound

TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting cites this paper.

TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 2018

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no resolver link, observed 2026-08-10T16:35:14.401552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 041d96c9-7bb8-4683-a7ee-749af8c41f80 · 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 SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 40

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verified exact
arxiv_id, observed 2026-05-23T02:52:26.567827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 0e690641-cb64-4122-86e7-89d5936872b7 · inbound

IRNN: Innovation-driven Recurrent Neural Network for Time-Series Data Modeling and Prediction cites this paper.

IRNN: Innovation-driven Recurrent Neural Network for Time-Series Data Modeling and Prediction SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 45

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no resolver link, observed 2026-08-15T23:00:11.184781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:00:11.184781Z digest=sha256:5ed2082c56bde2fc1fd4260be2f521d43d678083a3c18c474b20476e6bff4b34

Observation 2ef39792-64e7-41f2-9d88-216f92ab7471 · inbound

Temporal Query Network for Efficient Multivariate Time Series Forecasting cites this paper.

Temporal Query Network for Efficient Multivariate Time Series Forecasting SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 24

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no resolver link, observed 2026-08-15T20:28:50.133146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:28:50.133146Z digest=sha256:0a305739f2e6f6b5c938bd2fcedeaa87f181a7b1be6efe1dcade08d394e5ecef

Observation efbacd8b-9fad-4ddb-83f1-718a45417a25 · inbound

Human in the Loop Adaptive Optimization for Improved Time Series Forecasting cites this paper.

Human in the Loop Adaptive Optimization for Improved Time Series Forecasting SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 18

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no resolver link, observed 2026-08-07T15:23:59.807564Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:23:59.807564Z digest=sha256:3b2accd907c29fcecf319a64b96e178b246989da24812b1d43e07dc0ba150bbd

Observation f8ef571e-be57-4c57-aa33-4aa09fd2ed8c · 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 SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 30

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no resolver link, observed 2026-08-07T14:46:00.521271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:46:00.521271Z digest=sha256:e6c2fc7a16579ccf7517f1a44e60fc99de94dcfc23ca4b473e52b4fde8bb02b5

Observation 7f02ad7f-c3ab-4296-825c-4593164e6a33 · inbound

CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial Correlations cites this paper.

CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial Correlations SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 11

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no resolver link, observed 2026-08-07T14:25:03.845798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 71d8c771-4547-453e-bd3c-b0c49dc6d522 · inbound

Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectives cites this paper.

Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectives SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 59

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no resolver link, observed 2026-08-06T21:28:59.787950Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:28:59.787950Z digest=sha256:8860f2cf6fcd40dc51a73200debc868b760e3515987b02c21bfb225ec514d725

Observation 54688422-659d-40b4-b9ac-77f79114e04b · inbound

MillGNN: Learning Multi-Scale Lead-Lag Dependencies for Multi-Variate Time Series Forecasting cites this paper.

MillGNN: Learning Multi-Scale Lead-Lag Dependencies for Multi-Variate Time Series Forecasting SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 15

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no resolver link, observed 2026-08-05T10:42:46.112458Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:42:46.112458Z digest=sha256:d83fa135751e81e47e7eab26d068d6ccae13d6b1545dd1c8cd6b7e51631712e9

Observation 5d0262da-abc4-4f38-a5ee-aaa9818e22be · inbound

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting cites this paper.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 22

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no resolver link, observed 2026-08-05T04:36:27.539769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T04:36:27.539769Z digest=sha256:b67e7e2a9df28c0faac52a78c82321adf841d40f30c7c3724c54b5edd7a8cbd8

Observation f2287e2f-fbed-401d-8830-5ec884e3fcba · inbound

Convolutionally Low-Rank Models with Modified Quantile Regression for Interval Time Series Forecasting cites this paper.

Convolutionally Low-Rank Models with Modified Quantile Regression for Interval Time Series Forecasting SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 1

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metadata mismatch
arxiv_id, observed 2026-05-10T08:37:53.938507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation ae213dff-3fc8-48a4-93f5-c333efca1c3e · inbound

AdaMamba: Adaptive Frequency-Gated Mamba for Long-Term Time Series Forecasting cites this paper.

AdaMamba: Adaptive Frequency-Gated Mamba for Long-Term Time Series Forecasting SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 18

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verified exact
arxiv_id, observed 2026-05-11T20:41:12.513329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 821d07dc-ee47-4ee0-b7cc-1a2e7e243fe6 · inbound

Federated Weather Modeling on Sensor Data cites this paper.

Federated Weather Modeling on Sensor Data SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 22

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verified exact
arxiv_id, observed 2026-05-11T15:47:08.353400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 8fd158f0-cd34-4610-ba6d-3f888318c957 · inbound

TimeGuard: Channel-wise Pool Training for Backdoor Defense in Time Series Forecasting cites this paper.

TimeGuard: Channel-wise Pool Training for Backdoor Defense in Time Series Forecasting SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 35

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verified exact
arxiv_id, observed 2026-05-22T05:31:07.647813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-22T05:29:52.758898Z digest=sha256:85d8a4c23a0420d88023e8be45678f710361d28f7dc9c85af2c29747f1978c0a

Observation 65f79c86-b5cd-4013-9f4b-60b49a671c46 · inbound

Bridging Classification and Reconstruction: Cooperative Time Series Anomaly Detection cites this paper.

Bridging Classification and Reconstruction: Cooperative Time Series Anomaly Detection SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 78

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verified exact
arxiv_id, observed 2026-06-29T22:24:00.014593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-29T22:21:33.969144Z digest=sha256:7cd45608b4d05e54e8357b3f1b3ed206401c54ea41011fab0d04f0a3341b0930

Observation 0d067f1c-0340-4f01-b079-94fbe3555d24 · inbound

Enhancing Irregular Time Series Forecasting with Continuous-Time Modeling Framework cites this paper.

Enhancing Irregular Time Series Forecasting with Continuous-Time Modeling Framework SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 153

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no resolver link, observed 2026-07-31T19:49:56.141911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9f24d879-1f07-49d9-9e42-4b675dcfddea · inbound

Beyond Magnitude and Shape: A Direction-Aware Loss for Time Series Forecasting cites this paper.

Beyond Magnitude and Shape: A Direction-Aware Loss for Time Series Forecasting SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 6

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unresolved
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Unavailable: canonical work link unavailable.

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