Paper Citation Record · LEDGER

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset

As of 20 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2411.09928.

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

pith.paper-citation-record.v1
2411.09928 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

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measured 43 of 43 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.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation 8cb1f1e9-c31e-4877-bd3f-ae3e7d73d92c · outbound

This paper cites Multi-variate time series forecasting on variable subsets,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Multi-variate time series forecasting on variable subsets,

Reference 1

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Observation 4bceaeea-c060-4449-bc4d-dd4347babdb3 · outbound

This paper cites Dish-ts: a general paradigm for alleviating distribution shift in time series forecast- ing,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Dish-ts: a general paradigm for alleviating distribution shift in time series forecast- ing,

Reference 2

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Observation e13a12e7-7cff-4b72-bc2f-3eed081b2a44 · outbound

This paper cites Deep learning for multivariate time series imputation: A survey,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Deep learning for multivariate time series imputation: A survey,

Reference 3

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Observation e95b8875-8ee5-4bbd-81da-b0b782180c9a · outbound

This paper cites The internet of things: An overview,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset The internet of things: An overview,

Reference 4

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Observation 0458051d-77d7-45b2-b639-4e968340f950 · outbound

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

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Time-series forecasting with deep learning: a survey,

Reference 5

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Observation 2a2fc1f4-ab8a-4441-b22e-fb552696d538 · outbound

This paper cites A comprehensive survey on imputation of missing data in internet of things,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset A comprehensive survey on imputation of missing data in internet of things,

Reference 6

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Observation 4015775c-ff89-4f51-adc5-a881cff14b42 · outbound

This paper cites Turn waste into wealth: On simultaneous clustering and cleaning over dirty data,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Turn waste into wealth: On simultaneous clustering and cleaning over dirty data,

Reference 7

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Observation f661900d-c59f-4d52-8fb9-8dee2280e256 · outbound

This paper cites Swapping repair for misplaced attribute values,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Swapping repair for misplaced attribute values,

Reference 8

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Observation 19c8e5ad-1ce1-47a1-9940-ae186d1952a4 · outbound

This paper cites Nearest neighbor ensemble,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Nearest neighbor ensemble,

Reference 9

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Observation 7c5c7e43-ce1e-4a00-9561-851481f02ea5 · outbound

This paper cites Learning individual models for imputation,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Learning individual models for imputation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:13:45.740711Z

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Observation 8b9eb68f-08fc-4341-8ba3-1362bbc0ae4c · outbound

This paper cites Csdi: Conditional score- based diffusion models for probabilistic time series imputation,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Csdi: Conditional score- based diffusion models for probabilistic time series imputation,

Reference 11

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Observation 2699c815-2a74-4d0a-8e7e-805749acd0f7 · outbound

This paper cites Saits: Self-attention-based imputation for time series,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Saits: Self-attention-based imputation for time series,

Reference 12

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Observation 2661b95a-d140-46e5-9260-e12fc9ee0f5d · outbound

This paper cites Con- necting the dots: Multivariate time series forecasting with graph neural networks,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Con- necting the dots: Multivariate time series forecasting with graph neural networks,

Reference 13

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Observation 5a832865-58bf-433e-8c0e-00d61cceab06 · outbound

This paper cites Attention is all you need,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Attention is all you need,

Reference 14

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Observation 68cfffcc-8557-4975-a066-8fb997a48c6f · outbound

This paper cites Beyond efficient transformer for long sequence time-series forecasting., 2021, 35,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Beyond efficient transformer for long sequence time-series forecasting., 2021, 35,

Reference 15

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Observation f94f2dc9-8a7d-4bc8-9885-afdeedb93b89 · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 16

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Observation 496521b0-61f6-4f6b-bf9d-63715032e0e3 · outbound

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

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Informer: Beyond efficient transformer for long sequence time-series forecasting,

Reference 17

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Observation 1b7b893b-0322-419a-9751-5892f55c5d7e · outbound

This paper cites Attention based spatial- temporal graph convolutional networks for traffic flow forecasting,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Attention based spatial- temporal graph convolutional networks for traffic flow forecasting,

Reference 18

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Observation 6bf5fbd1-68c8-4ae1-a6cc-046233901fdc · outbound

This paper cites TGCN: Time Domain Graph Convolutional Network for Multiple Objects Tracking.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset TGCN: Time Domain Graph Convolutional Network for Multiple Objects Tracking

Reference 19

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Observation 39c23dc0-dfbf-4017-b663-5d741ce17fcf · outbound

This paper cites Temporal regularized matrix factorization for high-dimensional time series prediction,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Temporal regularized matrix factorization for high-dimensional time series prediction,

Reference 20

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Observation 7ab225b4-b0ae-48f5-a5b2-93a08a81625d · outbound

This paper cites Generative semi-supervised learning for multivariate time series imputation,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Generative semi-supervised learning for multivariate time series imputation,

Reference 21

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Observation f96e98f2-1375-44af-b674-c4b943194b84 · outbound

This paper cites mice: Multivariate impu- tation by chained equations in r,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset mice: Multivariate impu- tation by chained equations in r,

Reference 22

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Observation 3cfe0efa-4814-4fd5-a906-d0ab07222bd8 · outbound

This paper cites Time series data and recent imputation techniques for missing data: A review,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Time series data and recent imputation techniques for missing data: A review,

Reference 23

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Observation ead3a6d4-c97d-4bf7-b744-8f5388466a7d · outbound

This paper cites Imputation of missing data in time series for air pollutants,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Imputation of missing data in time series for air pollutants,

Reference 24

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Observation 5434b3b7-12c2-42c1-84f2-f9e29dd8fb36 · outbound

This paper cites Time Series Data Imputation: A Survey on Deep Learning Approaches.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Time Series Data Imputation: A Survey on Deep Learning Approaches

Reference 25

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Observation 09b39c25-f64b-4ba2-8ed9-31db7b71401c · outbound

This paper cites Missing data imputation of magdas-9’s ground electromagnetism with supervised machine learning and con- ventional statistical analysis models,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Missing data imputation of magdas-9’s ground electromagnetism with supervised machine learning and con- ventional statistical analysis models,

Reference 26

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Observation fce62c5b-ee37-40e0-83c7-6c0be80c34e0 · outbound

This paper cites Recon- structing missing variables for multivariate time series forecasting via conditional generative flows,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Recon- structing missing variables for multivariate time series forecasting via conditional generative flows,

Reference 27

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Observation 83ec4361-1d51-4124-b757-8d3d9cee341a · outbound

This paper cites Spatial- temporal interplay in human mobility: A hierarchical reinforcement learning approach with hypergraph representation,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Spatial- temporal interplay in human mobility: A hierarchical reinforcement learning approach with hypergraph representation,

Reference 28

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Observation 1f2ac6f9-9240-48be-8435-7d87c2de209d · outbound

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

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 29

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Observation 9ec90ea4-6d68-43e0-9f69-355bddee5f26 · outbound

This paper cites Prottrans: Toward understanding the language of life through self-supervised learning,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Prottrans: Toward understanding the language of life through self-supervised learning,

Reference 30

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This paper cites Data2vec: A general framework for self-supervised learning in speech, vision and language,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Data2vec: A general framework for self-supervised learning in speech, vision and language,

Reference 31

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Observation 2b9006aa-c68f-4235-b610-74866bc8403e · outbound

This paper cites Unsupervised Representation Learning by Predicting Image Rotations.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Unsupervised Representation Learning by Predicting Image Rotations

Reference 32

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Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Time-contrastive networks: Self-supervised learning from video,

Reference 33

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This paper cites Self-supervised learning for videos: A survey,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Self-supervised learning for videos: A survey,

Reference 34

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Observation f5328145-e77c-451f-b2f5-c15413069016 · outbound

This paper cites Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects

Reference 35

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Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset A transformer-based framework for multivariate time series representation learning,

Reference 36

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This paper cites Pre-training enhanced spatial- temporal graph neural network for multivariate time series forecasting,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Pre-training enhanced spatial- temporal graph neural network for multivariate time series forecasting,

Reference 37

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This paper cites Time-series generative ad- versarial networks,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Time-series generative ad- versarial networks,

Reference 38

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This paper cites Contrastive learning based self-supervised time-series analysis,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Contrastive learning based self-supervised time-series analysis,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:13:45.586582Z

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This paper cites Self-supervised contrastive pre-training for time series via time-frequency consistency,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Self-supervised contrastive pre-training for time series via time-frequency consistency,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:13:45.578992Z

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Observation c1940b1a-97a3-4136-969f-3fea5ed8058e · outbound

This paper cites Self-supervised learning for time series analysis: Taxonomy, progress, and prospects,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Self-supervised learning for time series analysis: Taxonomy, progress, and prospects,

Reference 41

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Observation aefd1e51-b8c1-4efc-a88d-782411a594ca · outbound

This paper cites Spatio-temporal self-supervised learning for traffic flow prediction,.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Spatio-temporal self-supervised learning for traffic flow prediction,

Reference 42

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Observation 9f407ebd-a484-455a-a976-1f070fb585ef · outbound

This paper cites Deep Learning for Multivariate Time Series Imputation: A Survey.

Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset Deep Learning for Multivariate Time Series Imputation: A Survey

Reference 2024

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Pith citing papers

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