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Paper Citation Record · LEDGER

Why Do Time Series Models Need Long Context Windows?

As of 19 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 1 inbound Pith citation observation for arXiv:2606.01999.

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

pith.paper-citation-record.v1
2606.01999 v1

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T15:52:40.568646Z

measured 71 of 71 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T06:16:38.667888Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

70 of 70 outbound references displayed

  • verified exact13
  • verified fuzzy0
  • unresolved55
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f5684a33-6572-4698-84d5-24b15adb749d · outbound

This paper cites Autoformer: Decomposition transformers with auto- correlation for long-term series forecasting.Advances in neural information processing systems, 34:22419–22430, 2021.

Why Do Time Series Models Need Long Context Windows? Autoformer: Decomposition transformers with auto- correlation for long-term series forecasting.Advances in neural information processing systems, 34:22419–22430, 2021

Reference 1

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Observation 4779469c-75a1-44cd-b853-5100b9415201 · outbound

This paper cites Deep learning for time series forecasting: Tutorial and literature survey.ACM Computing Surveys, 55(6):1–36, 2022.

Why Do Time Series Models Need Long Context Windows? Deep learning for time series forecasting: Tutorial and literature survey.ACM Computing Surveys, 55(6):1–36, 2022

Reference 2

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Observation 49ba33d3-d43f-47ef-838c-b045d8d7d783 · outbound

This paper cites Deep Time Series Models: A Comprehensive Survey and Benchmark.

Why Do Time Series Models Need Long Context Windows? Deep Time Series Models: A Comprehensive Survey and Benchmark

Reference 3

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Observation d4938ab3-e27c-42c2-9633-909f338a2dc0 · outbound

This paper cites Some recent advances in forecasting and control.Journal of the Royal Statistical Society.

Why Do Time Series Models Need Long Context Windows? Some recent advances in forecasting and control.Journal of the Royal Statistical Society

Reference 4

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Observation 2905ad02-45ba-45f0-98fb-f2e6cc6ae934 · outbound

This paper cites Jeffrey L.

Why Do Time Series Models Need Long Context Windows? Jeffrey L

Reference 5

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doi, observed 2026-06-28T16:02:21.926700Z

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Observation cf9ff48e-fc90-48ad-a120-2f2bfcd1d04c · outbound

This paper cites Recurrent neural networks for time series forecasting: Current status and future directions.International Journal of Forecasting, 37(1):388–427, 2021.

Why Do Time Series Models Need Long Context Windows? Recurrent neural networks for time series forecasting: Current status and future directions.International Journal of Forecasting, 37(1):388–427, 2021

Reference 6

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Observation bea8914e-6b29-4083-a696-63f875716d7b · outbound

This paper cites Deepar: Probabilistic forecasting with autoregressive recurrent networks.International journal of forecasting, 36(3):1181–1191, 2020.

Why Do Time Series Models Need Long Context Windows? Deepar: Probabilistic forecasting with autoregressive recurrent networks.International journal of forecasting, 36(3):1181–1191, 2020

Reference 7

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Observation 907ed715-2ef0-4450-8c1e-630a992df14f · outbound

This paper cites The m4 competition: 100,000 time series and 61 forecasting methods.

Why Do Time Series Models Need Long Context Windows? The m4 competition: 100,000 time series and 61 forecasting methods

Reference 8

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correction dated 2021-05-19. Source: crossref record 10.1016/j.ijforecast.2021.01.013->10.1016/j.ijforecast.2019.04.014:correction, observed 2026-07-11T03:18:10.382131+00:00. This notice travels one citation hop only.

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Observation 80c714b0-21df-4bff-8c56-2b5ac6e9a410 · outbound

This paper cites Principles and algorithms for forecasting groups of time series: Locality and globality.International Journal of Forecasting, 37(4):1632–1653, 2021.

Why Do Time Series Models Need Long Context Windows? Principles and algorithms for forecasting groups of time series: Locality and globality.International Journal of Forecasting, 37(4):1632–1653, 2021

Reference 9

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Observation 2c3d59cc-4df5-4b5f-869a-ec1d416bdab9 · outbound

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

Why Do Time Series Models Need Long Context Windows? Informer: Beyond efficient transformer for long sequence time-series forecasting

Reference 10

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Observation e6eb06b6-e42a-4d0c-a31c-08f40622a024 · outbound

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

Why Do Time Series Models Need Long Context Windows? A time series is worth 64 words: Long-term forecasting with transformers

Reference 11

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Observation 30efab65-d03d-4d07-a40e-3ba876a0718b · outbound

This paper cites FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting.

Why Do Time Series Models Need Long Context Windows? FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting

Reference 12

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Observation 811f048b-41da-49be-b229-b9ae9f75523c · outbound

This paper cites Liu, and Schahram Dustdar.

Why Do Time Series Models Need Long Context Windows? Liu, and Schahram Dustdar

Reference 13

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Observation 52ea08ae-d605-40cb-8d75-d5b05028f15f · outbound

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

Why Do Time Series Models Need Long Context Windows? A decoder-only foundation model for time-series forecasting

Reference 14

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Observation ec91219c-8a2a-4950-bc69-0c13a9ea2458 · outbound

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

Why Do Time Series Models Need Long Context Windows? Unified training of universal time series forecasting transformers

Reference 15

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Observation e41681b8-fac3-4a2b-87d1-aa356dfef8fc · outbound

This paper cites MOMENT: A Family of Open Time-series Foundation Models.

Why Do Time Series Models Need Long Context Windows? MOMENT: A Family of Open Time-series Foundation Models

Reference 16

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Observation 6e006046-e36d-4803-b9a4-474e8bc07c51 · outbound

This paper cites Foundation models for time series analysis: A tutorial and survey.

Why Do Time Series Models Need Long Context Windows? Foundation models for time series analysis: A tutorial and survey

Reference 17

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Observation 1aa7e8ae-cfbd-4c17-a771-ee85f6905870 · outbound

This paper cites An explanation of in-context learning as implicit bayesian inference.

Why Do Time Series Models Need Long Context Windows? An explanation of in-context learning as implicit bayesian inference

Reference 18

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Observation 306d1a92-9c6d-4289-a426-131e713840c8 · outbound

This paper cites What learning algorithm is in-context learning? investigations with linear models.

Why Do Time Series Models Need Long Context Windows? What learning algorithm is in-context learning? investigations with linear models

Reference 19

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Observation c5c769bf-50ac-48e3-8809-8bf2030aa570 · outbound

This paper cites Transformers as algorithms: Generalization and stability in in-context learning.

Why Do Time Series Models Need Long Context Windows? Transformers as algorithms: Generalization and stability in in-context learning

Reference 20

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Observation fe4f94d2-cd27-4a0e-8079-c8049369bc1e · outbound

This paper cites What and how does in-context learning learn? bayesian model averaging, parameterization, and generalization.

Why Do Time Series Models Need Long Context Windows? What and how does in-context learning learn? bayesian model averaging, parameterization, and generalization

Reference 21

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Why Do Time Series Models Need Long Context Windows? Unresolved cited work

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Observation a2b19077-7524-4899-b782-9536036b0857 · outbound

This paper cites A Survey on In-context Learning.

Why Do Time Series Models Need Long Context Windows? A Survey on In-context Learning

Reference 23

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Observation 004e5bce-a6c5-4e00-84dd-cc1206d30037 · outbound

This paper cites Chronos-2: From Univariate to Universal Forecasting.

Why Do Time Series Models Need Long Context Windows? Chronos-2: From Univariate to Universal Forecasting

Reference 24

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Observation 839a97c1-cbb3-4acc-984f-91f0bd46617c · outbound

This paper cites Making and evaluating point forecasts.Journal of the American Statistical Association, 106 (494):746–762, 2011.

Why Do Time Series Models Need Long Context Windows? Making and evaluating point forecasts.Journal of the American Statistical Association, 106 (494):746–762, 2011

Reference 25

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Observation 94e961ac-a8f6-4d0b-9c77-b95c6e356391 · outbound

This paper cites Chapman and Hall/CRC, 1995.

Why Do Time Series Models Need Long Context Windows? Chapman and Hall/CRC, 1995

Reference 26

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Observation fc551a04-57f4-4b5a-aefe-f104e69dff0b · outbound

This paper cites Chan, Biao Zhang, Aleksandra Faust, and Hugo Larochelle.

Why Do Time Series Models Need Long Context Windows? Chan, Biao Zhang, Aleksandra Faust, and Hugo Larochelle

Reference 27

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Observation 0e7da235-9142-4415-8fee-91a0279d2609 · outbound

This paper cites Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901, 2020.

Why Do Time Series Models Need Long Context Windows? Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901, 2020

Reference 28

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Observation 5a2f9909-2acf-45d8-87ed-721ee54d4395 · outbound

This paper cites Moirai 2.0: When less is more for time series forecasting.

Why Do Time Series Models Need Long Context Windows? Moirai 2.0: When less is more for time series forecasting

Reference 29

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arxiv_id, observed 2026-07-01T21:56:16.547607Z

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Observation 0a50cf3a-defc-447c-b58f-f1af4fd551e1 · outbound

This paper cites Timer-xl: Long-context transformers for unified time series forecasting.

Why Do Time Series Models Need Long Context Windows? Timer-xl: Long-context transformers for unified time series forecasting

Reference 30

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Observation b48976fb-d179-4bc5-af4c-b09abead7280 · outbound

This paper cites Largest: A benchmark dataset for large-scale traffic forecasting.Advances in Neural Information Processing Systems, 36:75354–75371, 2023.

Why Do Time Series Models Need Long Context Windows? Largest: A benchmark dataset for large-scale traffic forecasting.Advances in Neural Information Processing Systems, 36:75354–75371, 2023

Reference 31

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Why Do Time Series Models Need Long Context Windows? Unresolved cited work

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Observation 24e8ddf7-ecac-4dbf-b6be-40e43e05fb89 · outbound

This paper cites On the properties of neural machine translation: Encoder -- decoder approaches.

Why Do Time Series Models Need Long Context Windows? On the properties of neural machine translation: Encoder -- decoder approaches

Reference 33

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doi, observed 2026-06-28T16:02:21.920698Z

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Observation 278dcc86-c801-41ba-9379-daab8ce0bb2d · outbound

This paper cites Are transformers effective for time series forecasting? In Proceedings of the AAAI conference on artificial intelligence, volume 37, pages 11121–11128, 2023.

Why Do Time Series Models Need Long Context Windows? Are transformers effective for time series forecasting? In Proceedings of the AAAI conference on artificial intelligence, volume 37, pages 11121–11128, 2023

Reference 34

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Observation 790b6331-8714-4fa7-aabd-1438ff3dd8f2 · outbound

This paper cites Tsmixer: An all-mlp architecture for time series forecast-ing.Transactions on Machine Learning Research, 2023.

Why Do Time Series Models Need Long Context Windows? Tsmixer: An all-mlp architecture for time series forecast-ing.Transactions on Machine Learning Research, 2023

Reference 35

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Observation c2967dc2-e5cb-4058-a5db-cdfa889bbfcb · outbound

This paper cites Moderntcn: A modern pure convolution structure for general time series analysis.

Why Do Time Series Models Need Long Context Windows? Moderntcn: A modern pure convolution structure for general time series analysis

Reference 36

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Observation 347055f6-af12-423f-a113-66b5a91567b6 · outbound

This paper cites Resurrecting recurrent neural networks for long sequences.

Why Do Time Series Models Need Long Context Windows? Resurrecting recurrent neural networks for long sequences

Reference 37

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Observation be3d658b-7d44-4b7c-91b1-359b46580bf3 · outbound

This paper cites Foundation Models for Time Series: A Survey.

Why Do Time Series Models Need Long Context Windows? Foundation Models for Time Series: A Survey

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Observation 70f00d92-d889-40df-b41d-fd63218d3a68 · outbound

This paper cites In-context fine-tuning for time-series foundation models.

Why Do Time Series Models Need Long Context Windows? In-context fine-tuning for time-series foundation models

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:b15a9d2d15707815d033767513340641c949f5cf38d4c6083f8fa81443e6339d

Observation a9586bb6-7c5a-4203-af4b-b0642d4c7924 · outbound

This paper cites Zero-Shot Time Series Forecasting with Covariates via In-Context Learning.

Why Do Time Series Models Need Long Context Windows? Zero-Shot Time Series Forecasting with Covariates via In-Context Learning

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:9828375b161c7d7c9c1fd8dff03d70ebdc8259db5ec883d4902beb8349bd2391

Observation b2e098b8-1913-4fd3-9e9c-1b525a4f286c · outbound

This paper cites Context is key: A benchmark for forecasting with essential textual information.

Why Do Time Series Models Need Long Context Windows? Context is key: A benchmark for forecasting with essential textual information

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:6993fca16c1a61cd092c10b635f0287c1be396db50abf37aa9d311800cabdd54

Observation e22eeffc-b6d6-482f-95a8-98dd7493cff6 · outbound

This paper cites In-context time series predictor.

Why Do Time Series Models Need Long Context Windows? In-context time series predictor

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:dec92ccce26cdd60627a7bf6b7d1a1fffb8205f304759aec888323f922b2a6a1

Observation fd0b4896-74ce-4c90-99a1-0efecc64d5fe · outbound

This paper cites A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting.

Why Do Time Series Models Need Long Context Windows? A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:66ee12f4cc2bbdd055403a79e2ff6fb6620ba7c6bdd8ef37f4d9b3b5a61c9457

Observation 4c7a9cfc-e65e-4243-bb45-988a90b872ac · outbound

This paper cites Taming local effects in graph-based spatiotempo- ral forecasting.Advances in Neural Information Processing Systems, 36:55375–55393, 2023.

Why Do Time Series Models Need Long Context Windows? Taming local effects in graph-based spatiotempo- ral forecasting.Advances in Neural Information Processing Systems, 36:55375–55393, 2023

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:3e498b55cd6a885c1cd3648842b31a2aea84ec44ac338ed087d174f66c2b7b7b

Observation 69c5dab3-0066-48ed-8372-1010c2f19249 · outbound

This paper cites On the regularization of learnable embeddings for time series forecasting.Transactions on Machine Learning Research, 2025.

Why Do Time Series Models Need Long Context Windows? On the regularization of learnable embeddings for time series forecasting.Transactions on Machine Learning Research, 2025

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:1bd5ade4c0ca9c52e91d89c8e67bc4363ad1f31663580543fae49055e2221b5e

Observation c18c84fe-d7c6-4a3f-adf6-9f8baab0e28b · outbound

This paper cites Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping.

Why Do Time Series Models Need Long Context Windows? Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping

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local_arxiv, observed 2026-07-01T21:56:16.536733Z

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:b0b44b6e745d0ff6e1de523aad3e5de4807ce98adc0b41ccb566be8b667c4593

Observation 11c4bac0-ee66-4676-805c-4f52fa817544 · outbound

This paper cites Graph-based virtual sensing from sparse and partial multivariate observations.

Why Do Time Series Models Need Long Context Windows? Graph-based virtual sensing from sparse and partial multivariate observations

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:ac67708a53fd3111dbc72db0bc64d951b517c442ea2d3699289c5f99592a9211

Observation 6033273f-9248-4c9b-8b21-79896d582080 · outbound

This paper cites GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation.

Why Do Time Series Models Need Long Context Windows? GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:497807d3a00bb68e93d3536df4194dda8bdbfbcc80db0b9bd8a148a84a6c8eca

Observation ec1bbcce-2917-4426-baec-bc68884abb0a · outbound

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

Why Do Time Series Models Need Long Context Windows? Timer: generative pre-trained transformers are large time series models

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:910c2f6db13ceb317e122b482a4e07cf67eac783c80ac1b95f14cf375e41c946

Observation ca449e82-ef4d-48e5-a610-7dab344f5378 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Why Do Time Series Models Need Long Context Windows? Adam: A Method for Stochastic Optimization

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local_arxiv, observed 2026-07-01T21:56:16.528231Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:c9c6f03bca0f257fa87ab9705efb1c75513d9e4f9a27bd2903637f9508826b67

Observation 8f262a39-213b-4887-b950-948b0bca06dc · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

Why Do Time Series Models Need Long Context Windows? Attention is all you need.Advances in neural information processing systems, 30, 2017

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:7c3fad527f3e574a67a048def5d6b52a097845d2352b3b4ce570ac382b3abb85

Observation 20051cca-e6ed-4990-ba88-9d28c1720221 · outbound

This paper cites Oreshkin, Dmitri Carpov, Nicolas Chapados, and Yoshua Bengio.

Why Do Time Series Models Need Long Context Windows? Oreshkin, Dmitri Carpov, Nicolas Chapados, and Yoshua Bengio

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:0c34fbdc8c486241747eb25f1d81a2f63ef91875924f49825a06fb88817c6f1e

Observation 2dfdacf2-4731-4535-a407-db4abbcb4862 · outbound

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

Why Do Time Series Models Need Long Context Windows? One fits all: Power general time series analysis by pretrained LM

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:e047f7172ceaf8fabfc58f0ddd832d82c3b7f30965b3ff21c0d011b8bd4e7f28

Observation b03d7474-32e7-4473-b894-727601838252 · outbound

This paper cites Lag-llama: Towards foundation models for time series forecasting.

Why Do Time Series Models Need Long Context Windows? Lag-llama: Towards foundation models for time series forecasting

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:5025ff3cd40c870c94e7bb52f9c6b173fc630e506f721ab9c6cb5fe0e5c37366

Observation 67b05acd-7808-483d-aeda-af83249a4e5f · outbound

This paper cites Chronos: Learning the language of time series.Transactions on Machine Learning Research, 2024.

Why Do Time Series Models Need Long Context Windows? Chronos: Learning the language of time series.Transactions on Machine Learning Research, 2024

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:1df593c652aafbc77ed124d7a7454aa17fd158e5429d8fc482832ecfe2edef9d

Observation cde26aa5-18ce-4c87-9837-159f53fa2c23 · outbound

This paper cites Language models are unsupervised multitask learners.OpenAI blog, 1(8):9, 2019.

Why Do Time Series Models Need Long Context Windows? Language models are unsupervised multitask learners.OpenAI blog, 1(8):9, 2019

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:043746e89cb8c294f3baba99730346a47eba90c858fe0ee610b37443eee16e3b

Observation 9a37cd8a-d48d-4dbd-babf-10fcc71052ec · outbound

This paper cites Description based text classification with reinforcement learning.

Why Do Time Series Models Need Long Context Windows? Description based text classification with reinforcement learning

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:08e3ffc0c199560743822ab58ee6598b9e82cb800807feaa47e9f3d2ba90b957

Observation 31101a1c-8902-4cd5-9c92-13a834f05f2c · outbound

This paper cites Finetuned language models are zero-shot learners.

Why Do Time Series Models Need Long Context Windows? Finetuned language models are zero-shot learners

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:5f19fb0e0a285829595132b5e8719ffeaf2778c38f33ddc7a610d596b8f259da

Observation 7b0d7f6d-f1cc-4400-b536-572f25737058 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022.

Why Do Time Series Models Need Long Context Windows? Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:dfea37eb108e7f227924968c4f186d076c82403c8f53a523ae8e988d7c28802b

Observation 430f7187-833c-4086-b347-defd04aa7ad2 · outbound

This paper cites Meta-learning via language model in-context tuning.

Why Do Time Series Models Need Long Context Windows? Meta-learning via language model in-context tuning

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:51aa7786280db25ad350a42ef4f4206682b34738dbb2a40451e8f9893beb99d9

Observation 403ee155-7ec5-4061-94a9-4c25f71b1cba · outbound

This paper cites Metaicl: Learning to learn in context.

Why Do Time Series Models Need Long Context Windows? Metaicl: Learning to learn in context

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:1ce98011eec0bcc54d2662962e2fa6001c141ba0775437c5b671246f3519ebbb

Observation 03299c5e-a650-4498-8f6a-3fb1cffce65e · outbound

This paper cites In-context pretraining: Language modeling beyond document boundaries.

Why Do Time Series Models Need Long Context Windows? In-context pretraining: Language modeling beyond document boundaries

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:babd1db8a05c1c4140593f6d976c651d86658f6641ab61ab76e8f12308848e0b

Observation 32344e8c-c483-4a41-8ccc-6163801608a6 · outbound

This paper cites Fforma: Feature-based forecast model averaging.International Journal of Forecasting, 36(1):86–92, 2020.

Why Do Time Series Models Need Long Context Windows? Fforma: Feature-based forecast model averaging.International Journal of Forecasting, 36(1):86–92, 2020

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:f859b108e5b57e1ba2033ee2a168ad10bd9e7e9cd79b78306ade246d1dfdee62

Observation 3f60d2b2-82f3-4a2b-b5d6-ec6fea287fc9 · outbound

This paper cites Learning to control fast-weight memories: An alternative to dynamic recurrent networks.

Why Do Time Series Models Need Long Context Windows? Learning to control fast-weight memories: An alternative to dynamic recurrent networks

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:abb0b078ba361b4785ecc1947477e9347d9c4340ba6964dc0ebf8b96afeb550c

Observation c4fd1b1a-681e-44f7-8e1b-bdd77ea3c6bf · outbound

This paper cites Hypernetworks.

Why Do Time Series Models Need Long Context Windows? Hypernetworks

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:4dc7b428cd075e1f911c5429cd7c3ac4598d0c599b9a8bfe6ae4e4ada0d50714

Observation f251934d-e3f1-4d10-84d6-59d48517f1c7 · outbound

This paper cites Meta-learning framework with applications to zero-shot time-series forecasting.

Why Do Time Series Models Need Long Context Windows? Meta-learning framework with applications to zero-shot time-series forecasting

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:513b0721218366a93223c8f7d9eb9137c5d22add34b6feb49e1c42950b71a996

Observation 93359524-0613-4363-9817-6ae21ab42334 · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks.

Why Do Time Series Models Need Long Context Windows? Model-agnostic meta-learning for fast adaptation of deep networks

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:7ed6f8e80b64b6d1477c116b15592858750dfa8aa074880c893142b89a727847

Observation 2fff45f0-adab-46de-baec-52cfd2663d7a · outbound

This paper cites Meta-learning how to forecast time series.

Why Do Time Series Models Need Long Context Windows? Meta-learning how to forecast time series

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source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:32f628421a4761645ac0868454ee642ee42c22b3095eb8ed57e60a8a0f31eeda

Observation f39b3266-318e-4876-82f7-97fb1875b01a · outbound

This paper cites Tailored Forecasting from Short Time Series via Meta-learning.

Why Do Time Series Models Need Long Context Windows? Tailored Forecasting from Short Time Series via Meta-learning

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arxiv_id, observed 2026-08-05T00:40:39.026315Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-28T15:52:40.568646Z digest=sha256:6b9e2fee0b587e65ff80ef6529fe911b56dd8ff5f69907e315ae16156052d5d4

Observation 74234971-ecc9-4d96-9b4d-9e4895f35bae · outbound

This paper cites TheMoiraifamily [ 15, 28] further extended the line of probabilistic foundation models with encoder-only and decoder-only architectures.

Why Do Time Series Models Need Long Context Windows? TheMoiraifamily [ 15, 28] further extended the line of probabilistic foundation models with encoder-only and decoder-only architectures

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arxiv_id, observed 2026-07-01T21:56:16.542727Z

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Pith citing papers

Observation 32668b1c-0bc7-44fb-941d-bd941a906742 · inbound

The Spectrum Is Not Enough: When Context Helps Time-Series Forecasting cites this paper.

The Spectrum Is Not Enough: When Context Helps Time-Series Forecasting Why Do Time Series Models Need Long Context Windows?

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source=arxiv_source observed=2026-08-02T06:16:38.667888Z digest=sha256:93a49589d2e8eb5243a68036e5e212b7f7bd122d752e7bbe86cde21b3f1b296b