Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-29T19:08:46.032236Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 0 inbound Pith citation observations for arXiv:2605.26562.
A citation records a reference. It does not transfer a finding from one paper to another.
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Source: paper_references, paper_reference_links, observed 2026-06-29T19:08:46.032236Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
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A source-named dated measurement, never combined with another source.
Source: cited_works
75 of 75 outbound references displayed
External citation measurements
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting 2009.Statistical methods for forecasting
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting In2022 IEEE 38th International Conference on Data Engineering (ICDE)
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Mamba: Linear-Time Sequence Modeling with Selective State Spaces
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting InForty-second International Conference on Machine Learning
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Zhang, Xiaoming Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, and Qingsong Wen
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Reformer: The Efficient Transformer
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Liu, and Schahram Dustdar
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting LH-Mix: Local Hierarchy Correlation Guided Mixup over Hierarchical Prompt Tuning
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Unresolved cited work
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting InThe eleventh international conference on learning representations
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures
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