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Paper Citation Record · LEDGER

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting

As of 8 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2508.07490.

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

pith.paper-citation-record.v1
2508.07490 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:09:32.674446Z

measured 35 of 35 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T05:16:39.129020Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

  • verified exact5
  • verified fuzzy8
  • unresolved21
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bfc3d38f-bc97-454d-8286-b4d64c53bf3f · outbound

This paper cites International Journal of Forecasting27(3), 822–844 (Jul 2011).

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting International Journal of Forecasting27(3), 822–844 (Jul 2011)

Reference 1

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b072aea4-14a1-4fc7-92e6-5dc2be73b32c · outbound

This paper cites Machine Learning 108, 913–944 (2019).

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Machine Learning 108, 913–944 (2019)

Reference 2

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Observation 4fe5e4dc-fc8c-4697-9460-cd7d7be14925 · outbound

This paper cites N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting

Reference 3

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Observation 10e15a6a-6de4-4084-8f78-a5ffe63d6b7b · outbound

This paper cites an unresolved cited work.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Unresolved cited work

Reference 4

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 014d6be1-f1e1-451f-9e86-f176702deb78 · outbound

This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 5

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Observation 7a4e1f38-af21-41f8-b01f-00af37736270 · outbound

This paper cites Long-term Forecasting with TiDE: Time-series Dense Encoder.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Long-term Forecasting with TiDE: Time-series Dense Encoder

Reference 6

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Observation d61ed02a-b142-4273-afc3-d00593e9f04e · outbound

This paper cites In: International conference on machine learning.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting In: International conference on machine learning

Reference 7

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Observation 9aafd280-4b00-424a-9f0e-2f28a4c6de70 · outbound

This paper cites Are KANs Effective for Multivariate Time Series Forecasting?.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Are KANs Effective for Multivariate Time Series Forecasting?

Reference 8

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Observation aedb834e-4c8c-4d72-aa66-f29927d567bf · outbound

This paper cites OTexts (May 2018), google-Books-ID: _bBhDwAAQBAJ.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting OTexts (May 2018), google-Books-ID: _bBhDwAAQBAJ

Reference 9

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5fe95468-9ef0-4506-ae47-4f9e2a8fdfe2 · outbound

This paper cites Neural Computation 3(1), 79–87 (Mar 1991).

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Neural Computation 3(1), 79–87 (Mar 1991)

Reference 10

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Observation 1da7bfbb-af31-49db-ae0d-230ce773ba66 · outbound

This paper cites International Journal of Forecasting 36(1), 167–177 (Jan 2020).

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting International Journal of Forecasting 36(1), 167–177 (Jan 2020)

Reference 11

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7e8dff39-309f-418b-bdf3-151fde4bcd1e · outbound

This paper cites Mixtral of Experts.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Mixtral of Experts

Reference 12

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Observation da177500-80a9-4e98-91af-5cf303e8e582 · outbound

This paper cites International Journal of Forecasting 37(4), 1748–1764 (2021).

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting International Journal of Forecasting 37(4), 1748–1764 (2021)

Reference 13

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Observation fe49cce9-2e1e-47c7-ad2e-5b5b8f0f25b3 · outbound

This paper cites Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts

Reference 14

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Observation 0fd6f11c-afc2-446e-b07e-f5e3ec309661 · outbound

This paper cites Journal of Forecasting 1(2), 111–153 (1982).

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Journal of Forecasting 1(2), 111–153 (1982)

Reference 15

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doi, observed 2026-08-05T22:09:32.767570Z

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Observation 46495315-aa5b-42d6-a07d-368662b4feef · outbound

This paper cites International Journal of Forecasting 16(4), 451–476 (Oct 2000).

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting International Journal of Forecasting 16(4), 451–476 (Oct 2000)

Reference 16

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Observation f45e225a-9b9c-4b4c-9210-0f63f3f3d05f · outbound

This paper cites International Journal of Forecast- ing 34(4), 802–808 (Oct 2018).

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting International Journal of Forecast- ing 34(4), 802–808 (Oct 2018)

Reference 17

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correction dated 2021-05-19. Source: crossref record 10.1016/j.ijforecast.2021.01.013->10.1016/j.ijforecast.2018.06.001:correction, observed 2026-07-11T03:18:10.360745+00:00. This notice travels one citation hop only.

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Observation cd5268ae-afa5-4d1e-af6d-98428b8056c4 · outbound

This paper cites International Journal of Forecasting38(4), 1346– 1364 (2022).

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting International Journal of Forecasting38(4), 1346– 1364 (2022)

Reference 18

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Observation 6b38dd00-42a2-4096-8824-9a284654d019 · outbound

This paper cites Artificial Intelligence Review 42, 275–293 (2014).

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Artificial Intelligence Review 42, 275–293 (2014)

Reference 19

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 774c9acd-3512-406c-9c67-65d5be8aff03 · outbound

This paper cites International Journal of Forecast- ing 37(4), 1632–1653 (Oct 2021).

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting International Journal of Forecast- ing 37(4), 1632–1653 (Oct 2021)

Reference 20

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Observation 1982f873-6072-4fae-9514-8b1a075b133d · outbound

This paper cites In: International Conference on Artificial Intelligence and Statistics.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting In: International Conference on Artificial Intelligence and Statistics

Reference 21

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation e259d3c5-aec7-47db-a473-f5a9d98076fb · outbound

This paper cites N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting N-BEATS: Neural basis expansion analysis for interpretable time series forecasting

Reference 22

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Observation 3bd0ab10-47b5-45be-82b8-1b4593f9c09b · outbound

This paper cites In: Proceedings of the 27th International Joint Conference on Artificial Intelligence.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting In: Proceedings of the 27th International Joint Conference on Artificial Intelligence

Reference 23

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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.

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Observation 8ca6aa8f-ed81-4294-9ef1-91dd8fc5e930 · outbound

This paper cites In: Proceedingsofthe35thInternationalConferenceonNeuralInformationProcessing Systems.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting In: Proceedingsofthe35thInternationalConferenceonNeuralInformationProcessing Systems

Reference 24

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 679733e1-f8f6-433f-8b14-fea25ddfeeda · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 25

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Observation 2978db32-6b1f-4303-a8fa-896eba7e4a14 · outbound

This paper cites Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts

Reference 26

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Observation ae2e55b3-1627-418b-b357-54399e4b82d9 · outbound

This paper cites International journal of forecasting36(1), 75–85 (2020).

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting International journal of forecasting36(1), 75–85 (2020)

Reference 27

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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.

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Observation 79175d75-a482-4b42-b9b3-0f525738fc2a · outbound

This paper cites an unresolved cited work.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Unresolved cited work

Reference 28

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Observation 5f3df07c-00c6-4cc5-9633-23655fca1fb1 · outbound

This paper cites box-jenkins methodology.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting box-jenkins methodology

Reference 29

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raw_fallback, observed 2026-08-05T22:09:33.117320Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 649c60a1-002f-4845-87c4-d83be07afe5c · outbound

This paper cites A Time Series is Worth Five Experts: Heterogeneous Mixture of Experts for Traffic Flow Prediction.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting A Time Series is Worth Five Experts: Heterogeneous Mixture of Experts for Traffic Flow Prediction

Reference 30

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Observation 27141aee-865c-4613-a485-10d8fd56043b · outbound

This paper cites Auxiliary-Loss-Free Load Balancing Strategy for Mixture-of-Experts.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Auxiliary-Loss-Free Load Balancing Strategy for Mixture-of-Experts

Reference 31

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Observation 25486d27-2e33-44d2-8bec-fd3c8231c974 · outbound

This paper cites TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis

Reference 32

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Observation 9cc9a2d0-ae1c-491a-a164-8c71c82cbeb7 · outbound

This paper cites In: 2023 IEEE/CVF International Conference on Com- puter Vision (ICCV).

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting In: 2023 IEEE/CVF International Conference on Com- puter Vision (ICCV)

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e4de63b1-eaf6-4ccf-8384-125537d1bb07 · outbound

This paper cites an unresolved cited work.

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting Unresolved cited work

Reference 34

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unresolved
raw_fallback, observed 2026-08-05T22:09:33.107876Z

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.

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Pith citing papers

Observation 46cc2ba2-0b7c-4f52-af4d-5687a6dbdf8f · inbound

Hopformer: Homogeneity-Pursuit Transformer for Time Series Forecasting cites this paper.

Hopformer: Homogeneity-Pursuit Transformer for Time Series Forecasting N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting

Reference 16

Resolution
unresolved
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Source-reported events for the cited work

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