The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting | Paper Citation Record

Observation 285fd53e-e300-4d76-8b71-bf1412e201a9 · outbound

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

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Informer: Beyond efficient transformer for long sequence time-series forecasting,

Reference 1

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Observation 04fc4dbe-5689-481e-90c6-7b7e80b91ed9 · outbound

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

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Autoformer: Decomposition transform- ers with auto-correlation for long-term series forecasting,

Reference 2

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Observation 795f50c6-46d3-4596-9215-1d586d6c04be · outbound

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

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Fedformer: Frequency en- hanced decomposed transformer for long-term series forecasting,

Reference 3

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Observation 5c4b6c06-bda2-45f4-b608-322ca418c43b · outbound

This paper cites A time series is worth 64 words: Long-term forecasting with transformers,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting A time series is worth 64 words: Long-term forecasting with transformers,

Reference 4

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Observation 24470776-ac26-4567-b135-421bcb41802b · outbound

This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 5

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Observation 13bcf5f8-85c5-4230-b493-b88f96aa7612 · outbound

This paper cites TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables

Reference 6

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Observation 1e11aba9-2c0a-4b1f-9ddd-8ff12491f50f · outbound

This paper cites Autoregressive moving-average attention mechanism for time series forecasting,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Autoregressive moving-average attention mechanism for time series forecasting,

Reference 7

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Observation 2fd6bcf1-25f3-4a91-a876-c66d17c4d107 · outbound

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

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Pyraformer: Low-complexity pyramidal attention for long-range time series modeling and forecasting,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:34.847325Z

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Observation e5e6122b-fcd9-465b-ad95-91a02a16c946 · outbound

This paper cites Temporal fusion transformers for interpretable multi-horizon time series forecasting,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Temporal fusion transformers for interpretable multi-horizon time series forecasting,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:34.746394Z

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Observation 219144e4-c5a2-4084-b8e8-6c1044139845 · outbound

This paper cites Pdformer: Propagation delay-aware dynamic long-range transformer for traffic flow prediction,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Pdformer: Propagation delay-aware dynamic long-range transformer for traffic flow prediction,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:34.598058Z

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Observation 870cd516-df43-44fd-bbcc-c41f27ea2d51 · outbound

This paper cites Basisformer: Attention-based time series forecasting with learnable and interpretable basis,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Basisformer: Attention-based time series forecasting with learnable and interpretable basis,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:34.463667Z

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Observation 8b070c2f-d220-4d23-8860-ff5134be04f2 · outbound

This paper cites Samformer: Unlocking the potential of transformers in time series forecasting with sharpness-aware minimization and channel-wise attention,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Samformer: Unlocking the potential of transformers in time series forecasting with sharpness-aware minimization and channel-wise attention,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:34.238975Z

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Observation 6084ccce-90ee-4ff1-a934-6e3469674a82 · outbound

This paper cites Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting

Reference 13

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Observation e3b8d7e1-9b72-4c59-83e8-02688f7a7647 · outbound

This paper cites Learning to rotate: Quaternion transformer for complicated periodical time series forecasting,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Learning to rotate: Quaternion transformer for complicated periodical time series forecasting,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:34.017976Z

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Observation 086d1bca-f0ec-4516-8a69-169c4e91ddc4 · outbound

This paper cites Forecasting natural gas consumption in istanbul using neural networks and multivariate time series methods,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Forecasting natural gas consumption in istanbul using neural networks and multivariate time series methods,

Reference 15

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Observation a3fda1d4-36e5-49bc-9293-e8c4498e17ba · outbound

This paper cites A review on time series forecasting techniques for building energy consumption,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting A review on time series forecasting techniques for building energy consumption,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:33.459034Z

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Observation 0dac1727-2346-4c62-a41b-076aaf714017 · outbound

This paper cites Presentation of a new hybrid approach for forecasting economic growth using artificial intelligence approaches,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Presentation of a new hybrid approach for forecasting economic growth using artificial intelligence approaches,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:33.271698Z

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Observation cd7f9ef7-799a-4ebc-8d7a-5d33f4d58c31 · outbound

This paper cites Web service recommendation based on time series forecasting and collaborative filtering,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Web service recommendation based on time series forecasting and collaborative filtering,

Reference 18

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Observation 11fd23fe-b3ca-4493-a2a4-473d7982d128 · outbound

This paper cites An econometric time series forecasting framework for web services recommendation,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting An econometric time series forecasting framework for web services recommendation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:32.981861Z

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Observation a7fff938-15e8-419f-8046-f430472fa65c · outbound

This paper cites Neural net time series forecasting framework for time-aware web services recommendation,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Neural net time series forecasting framework for time-aware web services recommendation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:32.767493Z

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Observation 7ee5e3cb-1f35-48fc-92d5-9898efc8ae66 · outbound

This paper cites Multivariate time series dataset for space weather data analytics,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Multivariate time series dataset for space weather data analytics,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:32.567127Z

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Observation 79a89079-7b5b-44c8-88b5-0b66f00c0b5e · outbound

This paper cites Transductive lstm for time-series prediction: An application to weather forecasting,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Transductive lstm for time-series prediction: An application to weather forecasting,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:32.343279Z

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Observation 727adb08-d751-4674-beae-56eb0b633c65 · outbound

This paper cites Chapter 16 - copula methods for forecasting multivariate time series,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Chapter 16 - copula methods for forecasting multivariate time series,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:31.930169Z

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Observation e1f7dab6-007e-4857-84cc-68a1c5b110f7 · outbound

This paper cites Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:31.694540Z

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Observation d9308b56-b5ba-43aa-a7a1-e42cc11fea82 · outbound

This paper cites Fredformer: Fre- quency debiased transformer for time series forecasting,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Fredformer: Fre- quency debiased transformer for time series forecasting,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:31.455796Z

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Observation a9b10124-3a0c-46e2-968a-74e06bc6fc36 · outbound

This paper cites Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 27

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Observation 27bdeb32-d01a-462a-abe9-9a63a24971ff · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 28

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Observation a7ce6d2b-c540-43e5-a8e4-d6c6fe3f1495 · outbound

This paper cites What language model architecture and pretraining objective works best for zero-shot generalization?.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting What language model architecture and pretraining objective works best for zero-shot generalization?

Reference 29

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Observation 8e675d1c-7d07-40a0-b69e-4270be5d16c1 · outbound

This paper cites Decoder-Only or Encoder-Decoder? Interpreting Language Model as a Regularized Encoder-Decoder.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Decoder-Only or Encoder-Decoder? Interpreting Language Model as a Regularized Encoder-Decoder

Reference 30

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Observation a023b1db-0d76-405f-80f2-b3ee1ceb058c · outbound

This paper cites Advancing Transformer Architecture in Long-Context Large Language Models: A Comprehensive Survey.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Advancing Transformer Architecture in Long-Context Large Language Models: A Comprehensive Survey

Reference 31

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This paper cites A review on large language models: Architectures, applications, taxonomies, open issues and challenges,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting A review on large language models: Architectures, applications, taxonomies, open issues and challenges,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:30.763084Z

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Observation 71ad005d-879a-4429-b6c6-1f44158d6fe5 · outbound

This paper cites Attention is all you need,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Attention is all you need,

Reference 33

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Observation a4cb961e-fc61-4216-871e-fd15000ca2d1 · outbound

This paper cites A transformer-based framework for multivariate time series representation learn- ing,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting A transformer-based framework for multivariate time series representation learn- ing,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:30.525875Z

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Observation 9f08df83-03ca-458e-80a3-d3d6aa5b95bd · outbound

This paper cites TSLANet: Rethinking Transformers for Time Series Representation Learning.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting TSLANet: Rethinking Transformers for Time Series Representation Learning

Reference 35

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This paper cites Are Self-Attentions Effective for Time Series Forecasting?.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Are Self-Attentions Effective for Time Series Forecasting?

Reference 36

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Observation e3888425-f112-476a-9895-df2041a59001 · outbound

This paper cites Transformers in Time Series: A Survey.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Transformers in Time Series: A Survey

Reference 37

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Observation 7e9c69a4-df69-4387-ba1a-64e0dc577446 · outbound

This paper cites Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis

Reference 38

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Observation 9a03fe0d-bcfa-4916-b7f2-0ffc2ad3d170 · outbound

This paper cites TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T16:35:26.093417Z

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Observation a1a40764-3d44-4966-8a9d-8bf1cf3757c2 · outbound

This paper cites Timesnet: Temporal 2d-variation modeling for general time series analysis,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Timesnet: Temporal 2d-variation modeling for general time series analysis,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:30.351232Z

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Observation 4f695944-fb56-4b7d-ac8b-e77642730a35 · outbound

This paper cites Language models are unsupervised multitask learners,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Language models are unsupervised multitask learners,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:30.168966Z

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Observation 1ec8aa1b-bdd6-4e10-bf73-2989a2b5e7b9 · outbound

This paper cites Learning a trajectory using adjoint functions and teacher forcing,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Learning a trajectory using adjoint functions and teacher forcing,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:29.963681Z

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Observation 0256fe8f-ecc1-445f-9ecf-8cb1f41fcafa · outbound

This paper cites Professor forcing: A new algorithm for training recurrent networks,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Professor forcing: A new algorithm for training recurrent networks,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:29.727229Z

Source-reported events for the cited work

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Observation 4ed33f21-4336-4568-8c36-c44eef56ac11 · outbound

This paper cites Reversible instance normalization for accurate time-series forecasting against distribution shift,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Reversible instance normalization for accurate time-series forecasting against distribution shift,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:29.524994Z

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Observation 9e0d6a77-5a0b-46ea-b7cc-b0eedd19c446 · outbound

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

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Are transformers effective for time series forecasting?

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:29.329049Z

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 ce34f604-2b74-4c81-9519-6313aea39750 · outbound

This paper cites Enhancing the locality and breaking the memory bottleneck of transformer on time series forecasting,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Enhancing the locality and breaking the memory bottleneck of transformer on time series forecasting,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:29.179416Z

Source-reported events for the cited work

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Observation 66990188-572f-4734-8819-8d44fe07a321 · outbound

This paper cites Unified training of universal time series forecasting transformers,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Unified training of universal time series forecasting transformers,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:29.053894Z

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Observation ac97064b-ada4-4040-b3f0-0d52b8a7d71d · outbound

This paper cites One fits all: Power general time series analysis by pretrained lm,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting One fits all: Power general time series analysis by pretrained lm,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:28.823727Z

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Observation b251a94f-b7bf-47f9-bb56-3d41c6fd08cd · outbound

This paper cites A decoder-only foundation model for time- series forecasting,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting A decoder-only foundation model for time- series forecasting,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:28.658209Z

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Observation deac71cf-12e8-45b4-bf85-b878edb7d75b · outbound

This paper cites Timer: Generative pre-trained transformers are large time series models,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Timer: Generative pre-trained transformers are large time series models,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:28.453858Z

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Observation e1b07135-0a7a-4ab6-a721-8eaa1057001d · outbound

This paper cites Detection of outliers using interquartile range technique from intrusion dataset,.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Detection of outliers using interquartile range technique from intrusion dataset,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:28.318398Z

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 5b4d5561-aafd-4eb1-91fb-b842aa262cf5 · outbound

This paper cites Available: https://www.sciencedirect.com/science/article/pii/ S0893608020300010.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Available: https://www.sciencedirect.com/science/article/pii/ S0893608020300010

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:32.172953Z

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 3ecbc1ff-71a1-4661-852b-7e15014607bd · outbound

This paper cites ETSformer: Exponential Smoothing Transformers for Time-series Forecasting.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T16:35:25.081820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers