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Paper Citation Record · LEDGER

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching

As of 12 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2501.10448.

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

pith.paper-citation-record.v1
2501.10448 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:36:35.037015Z

measured 56 of 56 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

56 of 56 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 825d222f-3dce-4996-9898-35aa31312449 · outbound

This paper cites Multi-horizon in- flation forecasts using disaggregated data,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Multi-horizon in- flation forecasts using disaggregated data,

Reference 1

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Observation 76e085fe-1bd5-4610-81db-a0be566d2208 · outbound

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

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Multivariate time series dataset for space weather data analytics,

Reference 2

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Observation 25cc2c16-7ab4-42f5-ac15-d714e054023a · outbound

This paper cites Electric load forecasting using an artificial neural network,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Electric load forecasting using an artificial neural network,

Reference 3

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Observation 474c4a5a-20d2-4822-b58e-9ce2fb9fa1ce · outbound

This paper cites Context-aware path ranking in road networks,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Context-aware path ranking in road networks,

Reference 4

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Observation 6f3d8716-070c-402a-af76-1dd58a4da8ab · outbound

This paper cites Ultraman: A unified platform for big trajectory data management and analytics,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Ultraman: A unified platform for big trajectory data management and analytics,

Reference 5

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Source-reported events for the cited work

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Observation ce2b3067-f659-4bc9-a3fb-bbd56ef0065f · outbound

This paper cites Real-time distributed co-movement pattern detection on streaming trajectories,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Real-time distributed co-movement pattern detection on streaming trajectories,

Reference 6

Resolution
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Source-reported events for the cited work

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Observation 2a9d7651-7f8d-4bc5-927f-fb9404759077 · outbound

This paper cites Freeway performance measurement system: mining loop detector data,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Freeway performance measurement system: mining loop detector data,

Reference 7

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Source-reported events for the cited work

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Observation 5b95f390-f52f-4602-8bb8-ab746a305175 · outbound

This paper cites Mdtp: A multi-source deep traffic prediction framework over spatio-temporal trajectory data,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Mdtp: A multi-source deep traffic prediction framework over spatio-temporal trajectory data,

Reference 8

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Source-reported events for the cited work

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Observation 5bfe429f-a682-4d0e-8daa-293a4f14845f · outbound

This paper cites Unsupervised path representation learning with curriculum negative sampling,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Unsupervised path representation learning with curriculum negative sampling,

Reference 9

Resolution
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Source-reported events for the cited work

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Observation 1963ca76-a1ea-493c-869a-099c1dc608ba · outbound

This paper cites Team: Topological evolution-aware framework for traffic forecasting,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Team: Topological evolution-aware framework for traffic forecasting,

Reference 10

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Source-reported events for the cited work

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Observation a02f2824-7b29-4ec5-8bf8-b0a707d8eae2 · outbound

This paper cites Multivariate time- series modeling for forecasting sintering temperature in rotary kilns using dcgnet,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Multivariate time- series modeling for forecasting sintering temperature in rotary kilns using dcgnet,

Reference 11

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Source-reported events for the cited work

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Observation 1eb85d39-c9da-4f6b-a9a6-24f57afdf719 · outbound

This paper cites An edge-ai based forecasting approach for improving smart microgrid efficiency,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching An edge-ai based forecasting approach for improving smart microgrid efficiency,

Reference 12

Resolution
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Source-reported events for the cited work

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Observation 3d0b5a14-bcda-47d3-bd46-d8e578f57d9e · outbound

This paper cites Weakly guided adaptation for robust time series forecasting,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Weakly guided adaptation for robust time series forecasting,

Reference 13

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Source-reported events for the cited work

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Observation 33514926-67c1-4e50-9dec-7a5a2f0f888e · outbound

This paper cites AutoCTS+: Joint neural architecture and hyperparameter search for correlated time series forecasting,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching AutoCTS+: Joint neural architecture and hyperparameter search for correlated time series forecasting,

Reference 14

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Source-reported events for the cited work

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Observation 491898fe-d423-41eb-940d-6c531e368003 · outbound

This paper cites AutoCTS++: zero-shot joint neural architecture and hyperparameter search for correlated time series forecasting,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching AutoCTS++: zero-shot joint neural architecture and hyperparameter search for correlated time series forecasting,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 67a5a664-a99c-4afd-8474-f6c255fbcb49 · outbound

This paper cites TFB: towards comprehensive and fair benchmarking of time series forecasting methods,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching TFB: towards comprehensive and fair benchmarking of time series forecasting methods,

Reference 16

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Source-reported events for the cited work

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Observation 20dcf624-0ba4-4381-8bad-8a65723a501a · outbound

This paper cites Qcore: Data-efficient, on-device continual calibration for quantized models,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Qcore: Data-efficient, on-device continual calibration for quantized models,

Reference 17

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Source-reported events for the cited work

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Observation b1b3e929-9001-4038-8379-0536c73752bc · outbound

This paper cites Less is more: Efficient time series dataset condensation via two-fold modal matching,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Less is more: Efficient time series dataset condensation via two-fold modal matching,

Reference 18

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Source-reported events for the cited work

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Observation bcc7584b-6353-4665-a528-d1582f096666 · outbound

This paper cites Multiple time series forecasting with dynamic graph modeling,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Multiple time series forecasting with dynamic graph modeling,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 0ffed5da-e3ea-46db-8e2a-c659269ca413 · outbound

This paper cites Finding structure in time,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Finding structure in time,

Reference 20

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Source-reported events for the cited work

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Observation e0e49987-7c21-4f25-af81-da8640de777a · outbound

This paper cites Long short-term memory,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Long short-term memory,

Reference 21

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Source-reported events for the cited work

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Observation 5400b094-e247-4b05-b9e8-6102c97e5248 · outbound

This paper cites DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks

Reference 22

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Source-reported events for the cited work

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Observation bc27f46a-5370-4f8e-b96e-152989c9e778 · outbound

This paper cites Attention is all you need,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Attention is all you need,

Reference 23

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Source-reported events for the cited work

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Observation 35685f75-094a-429f-aeae-f95cdd91ee6e · outbound

This paper cites Pathformer: Multi-scale transformers with adaptive pathways for time series forecasting,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Pathformer: Multi-scale transformers with adaptive pathways for time series forecasting,

Reference 24

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation d077b0c5-33b6-46ef-8770-de04f8167ed4 · outbound

This paper cites Language models are unsupervised multitask learners,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Language models are unsupervised multitask learners,

Reference 25

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Source-reported events for the cited work

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Observation 4e7a7f9c-e9ce-4011-b560-410caab8a0ef · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 26

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation fc756eab-27c1-40c8-9752-874077489bad · outbound

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

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Informer: Beyond efficient transformer for long sequence time-series forecasting,

Reference 27

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 46ae06db-9f2f-4d1f-9d25-93a5676fcffa · outbound

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

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation aec9ae12-30f8-4a38-8394-1b8d79f7f9ea · outbound

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

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Fedformer: Frequency enhanced decomposed transformer for long-term series fore- casting,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 722f2b6f-0fe5-4dd7-8e29-425268c4d852 · outbound

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

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Are transformers effective for time series forecasting?

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 950b0bde-c556-46b5-ab3e-a7695cd5037e · outbound

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

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching A time series is worth 64 words: Long-term forecasting with transformers,

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 2bfafe72-8f3d-45eb-bf85-eb935eff5e9b · outbound

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

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Crossformer: Transformer utilizing cross- dimension dependency for multivariate time series forecasting,

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 90361309-ce21-4e9d-a55d-21e32ba286fe · outbound

This paper cites Tsmixer: Lightweight mlp-mixer model for multivariate time series forecasting,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Tsmixer: Lightweight mlp-mixer model for multivariate time series forecasting,

Reference 33

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raw_fallback, observed 2026-08-10T20:36:35.467442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 729282e5-c95f-4749-baef-5386c04fba94 · outbound

This paper cites Designing and training of lightweight neural networks on edge devices using early halting in knowledge distillation,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Designing and training of lightweight neural networks on edge devices using early halting in knowledge distillation,

Reference 34

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 55ba19a3-0cc3-4645-9c94-7b6e17e7490f · outbound

This paper cites Adapyramid: Adaptive pyramid for accelerating high-resolution object detection on edge devices,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Adapyramid: Adaptive pyramid for accelerating high-resolution object detection on edge devices,

Reference 35

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 322a335d-4c72-49e9-80eb-6fdec6b54764 · outbound

This paper cites A novel approach for seamless probabilistic photovoltaic power forecasting covering multi- ple time frames,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching A novel approach for seamless probabilistic photovoltaic power forecasting covering multi- ple time frames,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:36:35.420362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 8d4385ae-8d09-4e49-93f6-f3617bb40ebc · outbound

This paper cites CGF: A category guidance based pm$ {2.5}$ sequence forecasting training framework,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching CGF: A category guidance based pm$ {2.5}$ sequence forecasting training framework,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:36:35.405394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation aacece13-16f8-470d-9342-9038bc4f5099 · outbound

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

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching A transformer-based framework for multivariate time series representation learning,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:36:35.390203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 8486ce53-cb4e-4255-bb95-b6862255663e · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T20:36:34.956460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6867df39-eb60-496d-9df0-eda0bbf051cd · outbound

This paper cites A Multi-Horizon Quantile Recurrent Forecaster.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching A Multi-Horizon Quantile Recurrent Forecaster

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T20:36:34.960950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c1435172-0395-4835-bcfe-60d16ebc6b35 · outbound

This paper cites A dual-stage attention-based recurrent neural network for time series prediction,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching A dual-stage attention-based recurrent neural network for time series prediction,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:36:35.375600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation a9ca7da9-384e-4abd-9a8c-145516cf5ff3 · outbound

This paper cites Think globally, act locally: A deep neural network approach to high-dimensional time series forecasting,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Think globally, act locally: A deep neural network approach to high-dimensional time series forecasting,

Reference 42

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation c08fe3b8-b366-40ad-9284-9c3a4cebaf44 · outbound

This paper cites Reformer: The efficient transformer,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Reformer: The efficient transformer,

Reference 43

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 0dac3980-07ad-4eca-be68-57ef8cf068fa · outbound

This paper cites Towards long-term time-series forecasting: Feature, pattern, and distribution,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Towards long-term time-series forecasting: Feature, pattern, and distribution,

Reference 44

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 72381d10-078b-400d-b74d-a5733b5808cd · outbound

This paper cites Triformer: Triangular, variable-specific attentions for long sequence multivariate time series forecasting,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Triformer: Triangular, variable-specific attentions for long sequence multivariate time series forecasting,

Reference 45

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation e0b68191-30f5-4561-939d-d2f12b4702a4 · outbound

This paper cites itrans- former: Inverted transformers are effective for time series forecasting,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching itrans- former: Inverted transformers are effective for time series forecasting,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:36:35.299270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation e989280a-b305-4c9d-afac-ae2533539c12 · outbound

This paper cites TSMixer: An All-MLP Architecture for Time Series Forecasting.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching TSMixer: An All-MLP Architecture for Time Series Forecasting

Reference 47

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5848b73c-37c6-42ec-9b97-af33be6eaac4 · outbound

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

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Long-term Forecasting with TiDE: Time-series Dense Encoder

Reference 48

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c5b8d3e2-b136-47e7-b578-8cc7608a4a12 · outbound

This paper cites Lightts: Lightweight time series classification with adaptive ensemble distillation,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Lightts: Lightweight time series classification with adaptive ensemble distillation,

Reference 49

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 914b947a-50cb-49a0-bb55-416d3771f5f9 · outbound

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

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Multi-resolution expansion of analysis in time-frequency domain for time series forecasting,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:36:35.266069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 2da86d3c-740a-4096-9945-746e9809866f · outbound

This paper cites Timemixer: Decomposable multiscale mixing for time series forecasting,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Timemixer: Decomposable multiscale mixing for time series forecasting,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:36:35.250463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation a0ab6c04-0dbe-45f7-bdf3-ddcbe0201777 · outbound

This paper cites FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective

Reference 52

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 52787f63-5936-43ee-b3a2-b6ed76587a3f · outbound

This paper cites Disentangling structured components: Towards adaptive, interpretable and scalable time series forecasting,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Disentangling structured components: Towards adaptive, interpretable and scalable time series forecasting,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:36:35.234450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 03469d14-837b-4307-bf83-d170250a70ed · outbound

This paper cites Learning transferable visual models from natural language supervi- sion,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Learning transferable visual models from natural language supervi- sion,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:36:35.217453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation ea46cec4-53f3-4f3d-99c4-dd800be8b3e6 · outbound

This paper cites PETformer: Long-term Time Series Forecasting via Placeholder-enhanced Transformer.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching PETformer: Long-term Time Series Forecasting via Placeholder-enhanced Transformer

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-08-10T20:36:35.086032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation ebd82064-ce4e-4adf-a4d4-6a4fb0bee542 · outbound

This paper cites Decoupled weight decay regularization,.

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching Decoupled weight decay regularization,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:36:35.201641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Pith citing papers

No inbound Pith citation observations are available.