Paper Citation Record · LEDGER

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

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 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 14 of 14 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 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:23:59.807564Z

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

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 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

Resolution: 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 2026-08-09T06:31:02.800959+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-09T06:31:02.800959+00:00.

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

Resolution: 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 2026-08-09T06:31:02.800959+00:00.

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

Resolution: 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 2026-08-09T06:31:02.800959+00:00.

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

Resolution: 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 2026-08-09T06:31:02.800959+00:00.

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

Resolution: 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 2026-08-09T06:31:02.800959+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-04T19:31:41.456689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.