Paper Citation Record · LEDGER

Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 37 inbound Pith citation observations for arXiv:2207.01186.

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

pith.paper-citation-record.v1
2207.01186 v1

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 37 of 37 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 37 of 37 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:13:36.264664Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:36:25.760076Z

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External citation measurements

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Outbound references

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Pith citing papers

Observation 800d463f-99bf-4128-954d-1500f9e7841c · inbound

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models cites this paper.

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 124

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Source-reported events for the cited work

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Observation 17b3ab79-00a4-44f2-8843-bb20aaea3647 · inbound

A Hybrid Loss Framework for Decomposition-based Time Series Forecasting Methods: Balancing Global and Component Errors cites this paper.

A Hybrid Loss Framework for Decomposition-based Time Series Forecasting Methods: Balancing Global and Component Errors Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 14

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Observation 68390f0b-c96e-4bef-b17b-6cde12ba391d · inbound

TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection cites this paper.

TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 65

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Observation fa22438f-991d-4b6c-b15c-3f98db24803c · inbound

Tackling Data Heterogeneity in Federated Time Series Forecasting cites this paper.

Tackling Data Heterogeneity in Federated Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 5

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Observation a1d5a74d-8ee9-4ead-ae92-202f3526bfa5 · inbound

LeMoLE: LLM-Enhanced Mixture of Linear Experts for Time Series Forecasting cites this paper.

LeMoLE: LLM-Enhanced Mixture of Linear Experts for Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 2023

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Observation f0f75fae-774c-47c8-a807-7bfcc1ba45f6 · inbound

A Wave is Worth 100 Words: Investigating Cross-Domain Transferability in Time Series cites this paper.

A Wave is Worth 100 Words: Investigating Cross-Domain Transferability in Time Series Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 73

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Observation f8f98fe3-0a3d-4865-9b16-1522a41ce3c3 · inbound

LMS-AutoTSF: Learnable Multi-Scale Decomposition and Integrated Autocorrelation for Time Series Forecasting cites this paper.

LMS-AutoTSF: Learnable Multi-Scale Decomposition and Integrated Autocorrelation for Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 7

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Observation 080f1bcb-2140-481a-a5cb-83af745d3a77 · inbound

Federated Foundation Models on Heterogeneous Time Series cites this paper.

Federated Foundation Models on Heterogeneous Time Series Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 44

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Observation 7724c0ec-ac78-4390-8b35-447fec453ec1 · inbound

STTS-EAD: Improving Spatio-Temporal Learning Based Time Series Prediction via cites this paper.

STTS-EAD: Improving Spatio-Temporal Learning Based Time Series Prediction via Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 22

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Observation 7547b97e-4391-428d-abf0-d288dc5cf82f · inbound

Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting cites this paper.

Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 34

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Observation d07d40c6-9800-4d9a-a0a5-6ed99d41a0b4 · inbound

TSRM: A Lightweight Temporal Feature Encoding Architecture for Time Series Forecasting and Imputation cites this paper.

TSRM: A Lightweight Temporal Feature Encoding Architecture for Time Series Forecasting and Imputation Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 30

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Observation d8b6f415-9d29-4f7c-bb9b-4cbdef31bf59 · inbound

Retrieval Augmented Time Series Forecasting cites this paper.

Retrieval Augmented Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 9

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Observation d6aa2168-c99f-4e1e-a568-9eab2023290c · inbound

Logo-LLM: Local and Global Modeling with Large Language Models for Time Series Forecasting cites this paper.

Logo-LLM: Local and Global Modeling with Large Language Models for Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 13

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Observation cdde4d29-0402-47a1-bd5e-fcb111af9472 · inbound

Temporal Query Network for Efficient Multivariate Time Series Forecasting cites this paper.

Temporal Query Network for Efficient Multivariate Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 61

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Observation dd66ffb6-23ba-4dee-ae77-87c1f1b83cb3 · inbound

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting cites this paper.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 107

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Observation d63d10b0-8585-4d2e-b9fc-9a7673f46dfa · inbound

CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial Correlations cites this paper.

CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial Correlations Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 29

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Observation 3013d558-33ec-4939-954a-a22328d0d7b8 · inbound

TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state cites this paper.

TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 28

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Observation ad6f183c-e0cc-4e63-a71c-f4d538439a19 · inbound

UDuo: Universal Dual Optimization Framework for Online Matching cites this paper.

UDuo: Universal Dual Optimization Framework for Online Matching Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 11

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From Images to Signals: Are Large Vision Models Useful for Time Series Analysis? cites this paper.

From Images to Signals: Are Large Vision Models Useful for Time Series Analysis? Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 60

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FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting cites this paper.

FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 27

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Observation 9677c82f-e683-4df3-ad1b-0e15eedd8c56 · inbound

TFKAN: Time-Frequency KAN for Long-Term Time Series Forecasting cites this paper.

TFKAN: Time-Frequency KAN for Long-Term Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 27

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Observation 8b1f90a3-d114-4e10-83c7-d6c742fd3493 · inbound

Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectives cites this paper.

Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectives Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 131

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Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting cites this paper.

Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 56

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PRISM: Lightweight Multivariate Time-Series Classification through Symmetric Multi-Resolution Convolutional Layers cites this paper.

PRISM: Lightweight Multivariate Time-Series Classification through Symmetric Multi-Resolution Convolutional Layers Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-19T00:26:56.198360Z

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Observation 825b9886-1b68-48df-a3a0-e3a8befa4cbe · inbound

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting cites this paper.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 61

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CaReTS: A Multi-Task Framework Unifying Classification and Regression for Time Series Forecasting cites this paper.

CaReTS: A Multi-Task Framework Unifying Classification and Regression for Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 2023

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MSTN: A Lightweight and Fast Model for General TimeSeries Analysis cites this paper.

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 28

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Observation d384f244-ad69-4cd3-9377-b06388aae4e4 · inbound

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis cites this paper.

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-21T18:20:29.104144Z

Source-reported events for the cited work

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Observation d55b52af-0221-456f-94e5-a2dc7743f4d1 · inbound

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis cites this paper.

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 28

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Observation abe901eb-4778-4f94-bd44-a1383a6b1ddf · inbound

MambaSL: Exploring Single-Layer Mamba for Time Series Classification cites this paper.

MambaSL: Exploring Single-Layer Mamba for Time Series Classification Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:30:18.672019Z

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Observation 6605d21a-4c60-42ff-96a7-e387f8c37505 · inbound

Feature Anchors for Time-Series Sensor-Based Human Activity Recognition cites this paper.

Feature Anchors for Time-Series Sensor-Based Human Activity Recognition Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:56:13.557789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a0bfcec2-b119-449e-b449-7c0f7cac8a8d · inbound

PaP-NF: Probabilistic Long-Term Time Series Forecasting via Prefix-as-Prompt Reprogramming and Normalizing Flows cites this paper.

PaP-NF: Probabilistic Long-Term Time Series Forecasting via Prefix-as-Prompt Reprogramming and Normalizing Flows Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 26

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b19032be-7d64-4f63-b660-5619dbfb6233 · inbound

Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting cites this paper.

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

Reference 70

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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AnchorMoE: Interpretable Time Series Classification via Anchor-Routed MoE cites this paper.

AnchorMoE: Interpretable Time Series Classification via Anchor-Routed MoE Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:36:25.761874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cf46e019-f8bc-44ea-9a93-0e5bc48d0463 · inbound

AnchorMoE: Interpretable Time Series Classification via Anchor-Routed MoE cites this paper.

AnchorMoE: Interpretable Time Series Classification via Anchor-Routed MoE Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 60

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Observation 3f586564-1fa3-482a-a411-37802a1005f6 · inbound

Modular Foundation Models for Time-Series Perception in Digital Twins cites this paper.

Modular Foundation Models for Time-Series Perception in Digital Twins Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 153

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Observation 53afc1a3-05c3-4bc8-a469-e635cee06aa1 · inbound

Beyond Magnitude and Shape: A Direction-Aware Loss for Time Series Forecasting cites this paper.

Beyond Magnitude and Shape: A Direction-Aware Loss for Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 2022

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