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Paper Citation Record · LEDGER

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting

As of 9 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 1 inbound Pith citation observation for arXiv:2509.10324.

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

pith.paper-citation-record.v1
2509.10324 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T17:55:54.227868Z

measured 20 of 20 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T17:55:54.171229Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

19 of 19 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved18
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 71c3cde8-7291-4a29-b6b9-dd0887ff9782 · outbound

This paper cites Time series forecasting has moved beyond simply predicting weather or traffic, and is being used to learn patterns from any data that has an order to produce results.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Time series forecasting has moved beyond simply predicting weather or traffic, and is being used to learn patterns from any data that has an order to produce results

Reference 1

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Observation 9b497da5-37e8-4bec-9e1e-f8ab71864b40 · outbound

This paper cites ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting

Reference 2

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Observation e9d9abce-1971-46c7-80e7-00bb0dbaea68 · outbound

This paper cites an unresolved cited work.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Unresolved cited work

Reference 3

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Observation 19421a85-4a35-4fd5-b9a0-3f23fd4be40b · outbound

This paper cites an unresolved cited work.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-04T17:55:54.178749Z digest=sha256:13571d4430e49dd333df3ef1af3db8cc840fe09c41ca27e0e2e567bb9e87892a

Observation b038c9c4-ac47-4314-9071-20718b3024c4 · outbound

This paper cites Attention is all you need,.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Attention is all you need,

Reference 5

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source=pdf_text observed=2026-08-04T17:55:54.182112Z digest=sha256:dc28cc7a1fa33d4ec3261bc22770d68fb100b4d6fc8a3131f999313def0fba53

Observation 7dbb02d2-b4da-4759-a236-119ed9178189 · outbound

This paper cites An image is worth 16x16 words: Trans- formers for image recognition at scale,.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting An image is worth 16x16 words: Trans- formers for image recognition at scale,

Reference 6

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Observation 74f9726b-3535-4fe9-a9b9-4f45cf760bba · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 7

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source=pdf_text observed=2026-08-04T17:55:54.189508Z digest=sha256:fc53c8c65e05fbee878cdf6fe9df53004f61cc06d3cf55df1af7fbf60371bbe9

Observation a1934c20-82e6-41ec-af17-e9fa7afa0fd7 · outbound

This paper cites Mamba: Linear-time sequence modeling with selective state spaces,.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Mamba: Linear-time sequence modeling with selective state spaces,

Reference 8

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source=pdf_text observed=2026-08-04T17:55:54.193390Z digest=sha256:0967cd6b162fc4c1b2ed3f8baaae1c8121251cca09b29a7c177895fa4a080c22

Observation 6b2040e4-d9f8-4568-bfe7-ac8453c04942 · outbound

This paper cites In- former: Beyond efficient transformer for long sequence time-series forecasting,.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting In- former: Beyond efficient transformer for long sequence time-series forecasting,

Reference 9

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source=pdf_text observed=2026-08-04T17:55:54.196605Z digest=sha256:06eb7f9ab67c08ee3283913a775a2b6da0681561758f9e9bca05735d95b52426

Observation 7a2d1f30-7cbb-44d0-965c-eab7957e67a6 · outbound

This paper cites Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting,.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting,

Reference 10

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Observation c220522c-e8eb-433b-945c-d8f177e78154 · outbound

This paper cites Fedformer: Frequency en- hanced decomposed transformer for long-term series forecasting,.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Fedformer: Frequency en- hanced decomposed transformer for long-term series forecasting,

Reference 11

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Observation 54b98f02-cbbd-4160-b39f-7baccbb3fb82 · outbound

This paper cites Time-moe: Billion- scale time series foundation models with mixture of ex- perts,.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Time-moe: Billion- scale time series foundation models with mixture of ex- perts,

Reference 12

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source=pdf_text observed=2026-08-04T17:55:54.206422Z digest=sha256:3980be166030455c6659aae6f25974489f033bb9e53670f4f46c8ec405a71bde

Observation a8bc6602-fde3-4bc7-bdc9-6ccc7f120e54 · outbound

This paper cites Mixture of experts for time series foundation models,.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Mixture of experts for time series foundation models,

Reference 13

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source=pdf_text observed=2026-08-04T17:55:54.209435Z digest=sha256:75f979f021908421a5222e1c180928c873b720c1a2cfc65d542a302b5e70059d

Observation 8a889ba3-768b-486d-aa99-5367490fdf42 · outbound

This paper cites Are transformers effective for time series forecasting?,.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Are transformers effective for time series forecasting?,

Reference 14

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Observation 03be440d-a062-48af-acef-c1675854e7c9 · outbound

This paper cites How Much Position Information Do Convolutional Neural Networks Encode?.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting How Much Position Information Do Convolutional Neural Networks Encode?

Reference 15

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Observation d8fc7fcd-8b65-41d2-b134-72321deba529 · outbound

This paper cites an unresolved cited work.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Unresolved cited work

Reference 16

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Observation 5704db22-ff2e-483a-b0bd-01fbeb49635e · outbound

This paper cites Modeling long-and short-term temporal patterns with deep neural networks,.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Modeling long-and short-term temporal patterns with deep neural networks,

Reference 17

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source=pdf_text observed=2026-08-04T17:55:54.222028Z digest=sha256:f606b50fd9e0ad35b7a478be1496160484602681a148d01ea0bc42eec08b0858

Observation b4adead4-904b-4d4b-8c6f-b3a39dfdd6aa · outbound

This paper cites Reversible in- stance normalization for accurate time-series forecast- ing against distribution shift,.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Reversible in- stance normalization for accurate time-series forecast- ing against distribution shift,

Reference 18

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Observation 10e2004c-d2fb-4a51-b388-e17a12a39cd0 · outbound

This paper cites Adaptive nor- malization for non-stationary time series forecasting: A temporal slice perspective,.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting Adaptive nor- malization for non-stationary time series forecasting: A temporal slice perspective,

Reference 19

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Pith citing papers

Observation 9b497da5-37e8-4bec-9e1e-f8ab71864b40 · inbound

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting cites this paper.

ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting ARMA Block: A CNN-Based Autoregressive and Moving Average Module for Long-Term Time Series Forecasting

Reference 2

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