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Paper Citation Record · LEDGER

Channel Normalization for Time Series Channel Identification

As of 22 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2506.00432.

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

pith.paper-citation-record.v1
2506.00432 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:12:17.123974Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

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

49 of 49 outbound references displayed

  • verified exact3
  • verified fuzzy22
  • unresolved24
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6a5b1168-79c2-4130-a871-6ebc6edb183a · outbound

This paper cites write newline.

Channel Normalization for Time Series Channel Identification write newline

Reference 1

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Observation 40d706c8-8f7f-4dfc-8560-1102f21a42a9 · outbound

This paper cites an unresolved cited work.

Channel Normalization for Time Series Channel Identification Unresolved cited work

Reference 2

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Observation c2297a21-1346-4871-8d6b-18040a05f156 · outbound

This paper cites R., and Hinton, G.

Channel Normalization for Time Series Channel Identification R., and Hinton, G

Reference 3

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Observation 1d39d461-d741-4621-a7b7-dd3671b20fef · outbound

This paper cites MambaTS: Improved Selective State Space Models for Long-term Time Series Forecasting.

Channel Normalization for Time Series Channel Identification MambaTS: Improved Selective State Space Models for Long-term Time Series Forecasting

Reference 4

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Observation 73709d75-c0a8-4ab5-ab9b-af26466110dd · outbound

This paper cites R., Chen, M., Rodrigues, M.

Channel Normalization for Time Series Channel Identification R., Chen, M., Rodrigues, M

Reference 5

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Observation 0ea79904-9576-4092-b13d-c65a8c7fb0ea · outbound

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

Channel Normalization for Time Series Channel Identification Freeway performance measurement system: mining loop detector data

Reference 6

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Observation 53b920f7-38ae-4665-8173-174974a06256 · outbound

This paper cites From Similarity to Superiority: Channel Clustering for Time Series Forecasting.

Channel Normalization for Time Series Channel Identification From Similarity to Superiority: Channel Clustering for Time Series Forecasting

Reference 7

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Observation 16063e94-daf1-4ff8-9e76-9aabbc439c2c · outbound

This paper cites O., and Pfister, T.

Channel Normalization for Time Series Channel Identification O., and Pfister, T

Reference 8

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Observation a8f039ba-efc1-4c86-829f-5460e57d0314 · outbound

This paper cites Learning on bandwidth constrained multi-source data with mimo-inspired dpp map inference.

Channel Normalization for Time Series Channel Identification Learning on bandwidth constrained multi-source data with mimo-inspired dpp map inference

Reference 9

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Observation 79c7ae1a-372f-49c8-a7a4-52c80949abab · outbound

This paper cites Sequence complementor: Complementing transformers for time series forecasting with learnable sequences.

Channel Normalization for Time Series Channel Identification Sequence complementor: Complementing transformers for time series forecasting with learnable sequences

Reference 10

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Observation 637b83b0-b09a-4f17-8358-8e473cd838d2 · outbound

This paper cites InjectTST: A Transformer Method of Injecting Global Information into Independent Channels for Long Time Series Forecasting.

Channel Normalization for Time Series Channel Identification InjectTST: A Transformer Method of Injecting Global Information into Independent Channels for Long Time Series Forecasting

Reference 11

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Observation 525592ef-1764-4afd-ae99-f6cd4f8cd0b2 · outbound

This paper cites Towards spatio-temporal aware traffic time series forecasting.

Channel Normalization for Time Series Channel Identification Towards spatio-temporal aware traffic time series forecasting

Reference 12

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Observation 776ca5a9-5d58-4372-a1da-4bb910b4c700 · outbound

This paper cites A hybrid residual dilated lstm and exponential smoothing model for midterm electric load forecasting.

Channel Normalization for Time Series Channel Identification A hybrid residual dilated lstm and exponential smoothing model for midterm electric load forecasting

Reference 13

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Observation af840d55-53ef-46ed-9905-d278db790a93 · outbound

This paper cites UniTS: A Unified Multi-Task Time Series Model.

Channel Normalization for Time Series Channel Identification UniTS: A Unified Multi-Task Time Series Model

Reference 14

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Observation d3ee1a76-cbc4-40a0-a3ab-3431a633a2ba · outbound

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

Channel Normalization for Time Series Channel Identification Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 15

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Observation 6949c477-cda1-4054-a5ba-772b16032506 · outbound

This paper cites The Capacity and Robustness Trade-off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecasting.

Channel Normalization for Time Series Channel Identification The Capacity and Robustness Trade-off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecasting

Reference 16

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Observation 61af0a9e-d90c-4354-8095-b59092f521b0 · outbound

This paper cites B., Ord, J.

Channel Normalization for Time Series Channel Identification B., Ord, J

Reference 17

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Source-reported events for the cited work

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Observation b0cc2bb9-7c95-4ba0-b8ca-ccb8c93eed97 · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift.

Channel Normalization for Time Series Channel Identification Batch normalization: Accelerating deep network training by reducing internal covariate shift

Reference 18

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Observation e2300530-2e5f-4ea8-9cc9-9a24fe50f0f3 · outbound

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

Channel Normalization for Time Series Channel Identification Reversible instance normalization for accurate time-series forecasting against distribution shift

Reference 19

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Observation e563a5bf-f98a-4e3c-b474-f252a2755f31 · outbound

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

Channel Normalization for Time Series Channel Identification Modeling long-and short-term temporal patterns with deep neural networks

Reference 20

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Observation b5b034c2-c5af-468d-b275-e26e1911b475 · outbound

This paper cites Sequential Order-Robust Mamba for Time Series Forecasting.

Channel Normalization for Time Series Channel Identification Sequential Order-Robust Mamba for Time Series Forecasting

Reference 21

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Observation d0c81215-9b21-4821-8bf5-f42d316f8897 · outbound

This paper cites Predicting best-selling new products in a major promotion campaign through graph convolutional networks.

Channel Normalization for Time Series Channel Identification Predicting best-selling new products in a major promotion campaign through graph convolutional networks

Reference 22

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Observation c35db987-a3c2-4592-bb26-2d4fe4928ed0 · outbound

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

Channel Normalization for Time Series Channel Identification Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping

Reference 23

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Observation 94357a63-854f-4e9b-8e30-c477ed9e834e · outbound

This paper cites Bi-Mamba+: Bidirectional Mamba for Time Series Forecasting.

Channel Normalization for Time Series Channel Identification Bi-Mamba+: Bidirectional Mamba for Time Series Forecasting

Reference 24

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Observation 27d9d406-30fa-416d-857c-e721935e359d · outbound

This paper cites Scinet: Time series modeling and forecasting with sample convolution and interaction.

Channel Normalization for Time Series Channel Identification Scinet: Time series modeling and forecasting with sample convolution and interaction

Reference 25

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Observation fbeba5ab-bf7d-40f6-8c71-c87d8a81baad · outbound

This paper cites itransformer: Inverted transformers are effective for time series forecasting.

Channel Normalization for Time Series Channel Identification itransformer: Inverted transformers are effective for time series forecasting

Reference 26

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Observation 25875379-3076-43ba-9f83-7ab5ee3d8ef5 · outbound

This paper cites FMamba: Mamba based on Fast-attention for Multivariate Time-series Forecasting.

Channel Normalization for Time Series Channel Identification FMamba: Mamba based on Fast-attention for Multivariate Time-series Forecasting

Reference 27

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Observation d61f5285-b1ea-458d-9e8b-224865da1898 · outbound

This paper cites and Gweon, H.

Channel Normalization for Time Series Channel Identification and Gweon, H

Reference 28

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Observation 5978563f-4f66-4aad-8a6f-accef4c9eb20 · outbound

This paper cites Channel-aware low-rank adaptation in time series forecasting.

Channel Normalization for Time Series Channel Identification Channel-aware low-rank adaptation in time series forecasting

Reference 29

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 278c4437-9c1b-484b-bbe1-435573683081 · outbound

This paper cites H., Sinthong, P., and Kalagnanam, J.

Channel Normalization for Time Series Channel Identification H., Sinthong, P., and Kalagnanam, J

Reference 30

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Observation 09703cbf-783c-4168-baa8-c683d252b086 · outbound

This paper cites Solar power data for integration studies.

Channel Normalization for Time Series Channel Identification Solar power data for integration studies

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation cadc66cb-371b-4407-a492-a331d3a5a110 · outbound

This paper cites Deep adaptive input normalization for time series forecasting.

Channel Normalization for Time Series Channel Identification Deep adaptive input normalization for time series forecasting

Reference 32

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 45f354ec-9451-4d58-8e8a-d2820c6f538a · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

Channel Normalization for Time Series Channel Identification Pytorch: An imperative style, high-performance deep learning library

Reference 33

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Observation 187f49b6-39be-4922-8faf-6dd1b62d78b4 · outbound

This paper cites Certain Relations between Mutual Information and Fidelity of Statistical Estimation.

Channel Normalization for Time Series Channel Identification Certain Relations between Mutual Information and Fidelity of Statistical Estimation

Reference 34

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 8a09b408-cec5-4f4d-9d6b-56e6248cb00d · outbound

This paper cites E., Hinton, G.

Channel Normalization for Time Series Channel Identification E., Hinton, G

Reference 35

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Unavailable: canonical work link unavailable.

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Observation 5a6c6d78-af31-43ff-90f4-00a0806c7cc6 · outbound

This paper cites and Joy, A.

Channel Normalization for Time Series Channel Identification and Joy, A

Reference 36

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T12:12:15.972814Z digest=sha256:f92a94638fb12b883c5d6a2b83f8c593406faec6a0626b795bafb3120bed9b80

Observation fad630f5-f765-4605-b811-499a1db31d92 · outbound

This paper cites Instance Normalization: The Missing Ingredient for Fast Stylization.

Channel Normalization for Time Series Channel Identification Instance Normalization: The Missing Ingredient for Fast Stylization

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f4c09062-8512-4c5b-a016-92826e8bedd7 · outbound

This paper cites and Hinton, G.

Channel Normalization for Time Series Channel Identification and Hinton, G

Reference 38

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 59135a74-918a-4f10-9a18-49cdf8fad73a · outbound

This paper cites N., Kaiser, ., and Polosukhin, I.

Channel Normalization for Time Series Channel Identification N., Kaiser, ., and Polosukhin, I

Reference 39

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unresolved
no resolver link, observed 2026-08-07T12:12:16.233571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:12:16.233571Z digest=sha256:317de8842a723ce13b12dc7b668da57d59b7f436d25f9b9dcd3b22615c507afa

Observation bd24aba7-3d4d-4571-84aa-f4de40732fb1 · outbound

This paper cites Is mamba effective for time series forecasting? Neurocomputing, 619: 0 129178, 2025.

Channel Normalization for Time Series Channel Identification Is mamba effective for time series forecasting? Neurocomputing, 619: 0 129178, 2025

Reference 40

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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 2026-08-22T06:32:14.747728+00:00.

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Observation 867ec7bd-120a-4766-b29c-0dffb8abc843 · outbound

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

Channel Normalization for Time Series Channel Identification Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting

Reference 41

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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 2026-08-22T06:32:14.747728+00:00.

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Observation e3dd65eb-6162-484b-aa79-c64849df9ead · outbound

This paper cites and He, K.

Channel Normalization for Time Series Channel Identification and He, K

Reference 42

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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 2026-08-22T06:32:14.747728+00:00.

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Observation fa3d5ec3-a561-48f1-ac6d-e63f2add7dca · outbound

This paper cites an unresolved cited work.

Channel Normalization for Time Series Channel Identification Unresolved cited work

Reference 43

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unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 4aa96864-acf1-444e-91b8-121eb344d620 · outbound

This paper cites Are transformers effective for time series forecasting? In AAAI, 2023.

Channel Normalization for Time Series Channel Identification Are transformers effective for time series forecasting? In AAAI, 2023

Reference 44

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 602d3de5-c857-465d-8d4f-a5fa9ef6d9f6 · outbound

This paper cites CMamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series Forecasting.

Channel Normalization for Time Series Channel Identification CMamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series Forecasting

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:16.783362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:12:16.783362Z digest=sha256:b24f15d2934b5fa1de8ca9228dcd01c37ee285b9465a36e1f04c5975d2123249

Observation fa2f1935-8932-477d-82c0-b750740ba2a9 · outbound

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

Channel Normalization for Time Series Channel Identification Informer: Beyond efficient transformer for long sequence time-series forecasting

Reference 46

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unresolved
no resolver link, observed 2026-08-07T12:12:16.816513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:12:16.816513Z digest=sha256:1e4f4e678d8df1ca5b50f5129fff875f0eee62381706b714ebe2866a4d442bee

Observation c7614e07-ee74-4f33-a75c-0d86ee30ae64 · outbound

This paper cites @esa (Ref.

Channel Normalization for Time Series Channel Identification @esa (Ref

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:16.905433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:12:16.905433Z digest=sha256:350653e7bf6a56864aef3bee65999c6e599b1af2bce1740b5ade275984eb24f3

Observation bb41a4a2-6ec7-44a2-bcf8-62038646fc0c · outbound

This paper cites an unresolved cited work.

Channel Normalization for Time Series Channel Identification Unresolved cited work

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:17.024462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:12:17.024462Z digest=sha256:dea86cb3bfc0974ea97d2f733d136d91a7f92ef14b114b55f92d62b7124836f3

Observation 809f68e1-b5d6-44d4-9d42-e4f6e8203914 · outbound

This paper cites an unresolved cited work.

Channel Normalization for Time Series Channel Identification Unresolved cited work

Reference 49

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unresolved
no resolver link, observed 2026-08-07T12:12:17.123974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:12:17.123974Z digest=sha256:90239e8acf4baea25b542475b8deaf71d8564a575f1d8428519aa0f2cf6b2611

Pith citing papers

No inbound Pith citation observations are available.