Paper Citation Record · LEDGER

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks

As of 20 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2505.20048.

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

pith.paper-citation-record.v1
2505.20048 v1

Coverage vector

measured 35 of 35 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-07T14:07:18.818987Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 51a1fb05-55aa-4125-a164-c37377390952 · outbound

This paper cites Climate Aware Deep Neural Networks (CADNN) for Wind Power Simulation.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Climate Aware Deep Neural Networks (CADNN) for Wind Power Simulation

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:07:19.042292Z

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Observation b0e89bca-0d90-43db-a28b-3d756245b665 · outbound

This paper cites Energy time series forecasting based on pattern sequence similarity,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Energy time series forecasting based on pattern sequence similarity,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:23.976431Z

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Observation 3af1ab60-e021-4523-b1e9-40a8e34fd999 · outbound

This paper cites Financial time series forecasting-a deep learning approach,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Financial time series forecasting-a deep learning approach,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:23.886727Z

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Observation a91a7e50-5001-4295-ac96-0a223af75aa3 · outbound

This paper cites Unveiling the multi- dimensional spatio-temporal fusion transformer (mdstft): A revolution- ary deep learning framework for enhanced multi-variate time series forecasting,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Unveiling the multi- dimensional spatio-temporal fusion transformer (mdstft): A revolution- ary deep learning framework for enhanced multi-variate time series forecasting,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:23.738339Z

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Observation 9bf1fe19-9461-4ad3-bf08-c382eb0a4664 · outbound

This paper cites Multi-resolution expansion of analysis in time-frequency domain for time series forecasting,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Multi-resolution expansion of analysis in time-frequency domain for time series forecasting,

Reference 5

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Observation 4f172f02-641f-4b28-9bbd-13f34b53c1d0 · outbound

This paper cites Compressive spatio-temporal forecasting of meteorological quantities and photo- voltaic power,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Compressive spatio-temporal forecasting of meteorological quantities and photo- voltaic power,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:23.342127Z

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Observation 337d09e3-8f51-4291-873c-e0ecc8b1f4bb · outbound

This paper cites Deep learning for time series forecasting: Tutorial and literature survey,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Deep learning for time series forecasting: Tutorial and literature survey,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:23.188610Z

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Observation 67df1b87-38f3-4b87-8435-beacce8a1cf6 · outbound

This paper cites Temporal convolutional neural (tcn) network for an effective weather forecasting using time-series data from the local weather station,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Temporal convolutional neural (tcn) network for an effective weather forecasting using time-series data from the local weather station,

Reference 8

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Observation f0729a79-e859-4799-8b08-97881c6b41ad · outbound

This paper cites Time-series forecasting with deep learning: a survey,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Time-series forecasting with deep learning: a survey,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:22.887373Z

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Observation a16dec00-907b-499b-a026-223a81a9fd7b · outbound

This paper cites Deep learning for time series forecasting: a survey,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Deep learning for time series forecasting: a survey,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:22.739375Z

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Observation 379b9887-d210-4c8b-93f9-1e4d6ffa7394 · outbound

This paper cites An experi- mental review on deep learning architectures for time series forecasting,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks An experi- mental review on deep learning architectures for time series forecasting,

Reference 11

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Observation ffc496d2-4286-4a0b-95b9-0620d40ba717 · outbound

This paper cites AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing

Reference 12

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Observation fd2f35de-c83e-411b-8274-e019efcb1384 · outbound

This paper cites Attention is all you need,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Attention is all you need,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:22.407780Z

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Observation 9649bcb3-51fc-4688-98ec-b1acc1dc9366 · outbound

This paper cites Transformers in vision: A survey,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Transformers in vision: A survey,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:22.240863Z

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Observation 7caefda3-c630-474a-9a98-c9c0bf99696b · outbound

This paper cites A comparative study on transformer vs rnn in speech applications,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks A comparative study on transformer vs rnn in speech applications,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:22.050911Z

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Observation 1d3e22c6-ccf5-4a74-8b8b-6aa81f74478e · outbound

This paper cites Transformers in Time Series: A Survey.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Transformers in Time Series: A Survey

Reference 16

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Observation 0a66cc7c-8dac-4c21-9851-4fd427420664 · outbound

This paper cites A practical survey on faster and lighter transformers,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks A practical survey on faster and lighter transformers,

Reference 17

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Observation d2006879-4d9d-4f7f-9838-9ebbbfae99dc · outbound

This paper cites Long-short transformer: Efficient transformers for language and vision,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Long-short transformer: Efficient transformers for language and vision,

Reference 18

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Observation 53e9ce2a-19da-48b8-b1a5-12ea556cd8ce · outbound

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

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Informer: Beyond efficient transformer for long sequence time-series forecasting,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:21.500676Z

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Observation 142c48ea-1700-4caf-ab02-f9a080f02525 · outbound

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

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Autoformer: Decomposition transformers with Auto-Correlation for long-term series forecasting,

Reference 20

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Observation 52b345fd-6905-43b0-ab91-c75459988596 · outbound

This paper cites FEDformer: Frequency enhanced decomposed transformer for long-term series fore- casting,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks FEDformer: Frequency enhanced decomposed transformer for long-term series fore- casting,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:21.134350Z

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Observation 16a9cd4e-ea7a-4613-8d49-422cd99a827e · outbound

This paper cites Pyraformer: Low-complexity pyramidal attention for long-range time series modeling and forecasting,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Pyraformer: Low-complexity pyramidal attention for long-range time series modeling and forecasting,

Reference 22

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Observation cce3e92f-e5e3-47f9-9e8b-9cc23f402d39 · outbound

This paper cites Are Transformers Effective for Time Series Forecasting?.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Are Transformers Effective for Time Series Forecasting?

Reference 23

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Observation 3014e666-5514-4613-81cb-6e36ccff3c81 · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 24

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

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks An image is worth 16x16 words: Trans- formers for image recognition at scale,

Reference 25

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This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representations,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:20.663743Z

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Observation a48b31ad-1433-4df2-9354-81f9bc0d5474 · outbound

This paper cites Time series clas- sification using multi-channels deep convolutional neural networks,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Time series clas- sification using multi-channels deep convolutional neural networks,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:20.474815Z

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Observation eec78c0f-91ff-4725-a739-761b6244ea9b · outbound

This paper cites Deep learning for universal linear embeddings of nonlinear dynamics,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Deep learning for universal linear embeddings of nonlinear dynamics,

Reference 28

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Observation 6d153f8e-834d-4738-bd8c-9f39dbd3120f · outbound

This paper cites Learning deep neural network representations for Koopman operators of nonlinear dynamical systems,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Learning deep neural network representations for Koopman operators of nonlinear dynamical systems,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:20.148423Z

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Observation 649715ab-a8d1-4383-ab35-8a52df798820 · outbound

This paper cites Learning Koopman invariant subspaces for dynamic mode decomposition,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Learning Koopman invariant subspaces for dynamic mode decomposition,

Reference 30

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Observation 6e81fe6a-62ce-46b3-a14b-b5d0a3edf44e · outbound

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Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Dissipative deep neural dynamical systems,

Reference 31

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Observation 225ed1fc-3d8a-4991-953c-5f4983dd866f · outbound

This paper cites Constrained block nonlinear neural dynamical models,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Constrained block nonlinear neural dynamical models,

Reference 32

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This paper cites On the stochastic stability of deep markov models,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks On the stochastic stability of deep markov models,

Reference 33

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Observation d71d18e1-c52f-41ab-afc6-fd7e39d34c40 · outbound

This paper cites Deep learning for universal linear embeddings of nonlinear dynamics,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Deep learning for universal linear embeddings of nonlinear dynamics,

Reference 34

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Observation a739f495-085f-4b70-800d-131c3084d309 · outbound

This paper cites Learning koopman invariant subspaces for dynamic mode decomposition,.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks Learning koopman invariant subspaces for dynamic mode decomposition,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:19.211063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

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