Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting | Paper Citation Record

Observation a527473e-953c-4eaa-86d3-c1fe6d99a968 · inbound

Deep Time Series Models: A Comprehensive Survey and Benchmark cites this paper.

Deep Time Series Models: A Comprehensive Survey and Benchmark Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 200

Resolution: verified exact; arxiv_id, observed 2026-05-23T23:05:51.427173Z

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Observation 2dac39d7-bd37-44d3-8131-3a4c168598e6 · inbound

Sundial: A Family of Highly Capable Time Series Foundation Models cites this paper.

Sundial: A Family of Highly Capable Time Series Foundation Models Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 19

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Time Series Representations for Classification Lie Hidden in Pretrained Vision Transformers cites this paper.

Time Series Representations for Classification Lie Hidden in Pretrained Vision Transformers Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 43

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Delayformer: spatiotemporal transformation for predicting high-dimensional dynamics cites this paper.

Delayformer: spatiotemporal transformation for predicting high-dimensional dynamics Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 53

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Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting cites this paper.

Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 13

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Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions cites this paper.

Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 2017

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Towards Foundation Auto-Encoders for Time-Series Anomaly Detection cites this paper.

Towards Foundation Auto-Encoders for Time-Series Anomaly Detection Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 30

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Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and Projection cites this paper.

Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and Projection Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 29

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Observation 479a8710-cf98-4e40-a316-a3fb6b439c14 · inbound

Time Series Foundation Models for Multivariate Financial Time Series Forecasting cites this paper.

Time Series Foundation Models for Multivariate Financial Time Series Forecasting Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 61

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Towards Interpretable Time Series Foundation Models cites this paper.

Towards Interpretable Time Series Foundation Models Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 15

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Foundation Models for Demand Forecasting via Dual-Strategy Ensembling cites this paper.

Foundation Models for Demand Forecasting via Dual-Strategy Ensembling Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 43

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Observation 9c9cefa9-ee62-4515-b4a9-e5184c703f6a · inbound

Foundation Models for Clean Energy Forecasting: A Comprehensive Review cites this paper.

Foundation Models for Clean Energy Forecasting: A Comprehensive Review Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 20

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Hallucination Detection and Mitigation with Diffusion in Multi-Variate Time-Series Foundation Models cites this paper.

Hallucination Detection and Mitigation with Diffusion in Multi-Variate Time-Series Foundation Models Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 7

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STARE: Predicting Decision Making Based on Spatio-Temporal Eye Movements cites this paper.

STARE: Predicting Decision Making Based on Spatio-Temporal Eye Movements Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 30

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On Identifying Why and When Foundation Models Perform Well on Time-Series Forecasting Using Automated Explanations and Rating cites this paper.

On Identifying Why and When Foundation Models Perform Well on Time-Series Forecasting Using Automated Explanations and Rating Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 38

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Beyond Accuracy: Are Time Series Foundation Models Well-Calibrated? cites this paper.

Beyond Accuracy: Are Time Series Foundation Models Well-Calibrated? Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 2020

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DeXposure-FM: A Time-series, Graph Foundation Model for Credit Exposures and Stability on Decentralized Financial Networks cites this paper.

DeXposure-FM: A Time-series, Graph Foundation Model for Credit Exposures and Stability on Decentralized Financial Networks Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 36

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Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables cites this paper.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 2019

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TempusBench: An Evaluation Framework for Time-Series Forecasting cites this paper.

TempusBench: An Evaluation Framework for Time-Series Forecasting Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:41:05.491159Z

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Observation 6cd754a2-fc66-48c5-b086-3e9bd0a13147 · inbound

Thermal-GEMs: Generalized Models for Building Thermal Dynamics cites this paper.

Thermal-GEMs: Generalized Models for Building Thermal Dynamics Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:15:48.539213Z

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Observation 9f45ae73-b525-4a40-986f-628b8e7627ac · inbound

Conditional Imputation for Within-Modality Missingness in Multi-Modal Federated Learning cites this paper.

Conditional Imputation for Within-Modality Missingness in Multi-Modal Federated Learning Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:36:09.681862Z

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Observation 24ee010b-b73f-4c62-a680-44cdcd149227 · inbound

Heterogeneous Scientific Foundation Model Collaboration cites this paper.

Heterogeneous Scientific Foundation Model Collaboration Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 78

Resolution: verified exact; arxiv_id, observed 2026-05-09T04:30:11.489892Z

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Observation 4a1dd461-b541-4510-bcf9-d4396829e0b4 · inbound

Explainable Load Forecasting with Covariate-Informed Time Series Foundation Models cites this paper.

Explainable Load Forecasting with Covariate-Informed Time Series Foundation Models Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-09T04:40:12.863715Z

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Observation 909595d6-8c2d-4225-8193-385b75d92ec0 · inbound

FactoryNet: A Large-Scale Dataset toward Industrial Time-Series Foundation Models cites this paper.

FactoryNet: A Large-Scale Dataset toward Industrial Time-Series Foundation Models Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 22

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Observation b528c366-cd8c-4c92-9b26-88e09bbd604a · inbound

FactoryNet: A Large-Scale Dataset toward Industrial Time-Series Foundation Models cites this paper.

FactoryNet: A Large-Scale Dataset toward Industrial Time-Series Foundation Models Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 22

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Observation 0cb05c77-31b2-4014-95b6-882cb3518250 · inbound

TimeClaw: A Time-Series AI Agent with Exploratory Execution Learning cites this paper.

TimeClaw: A Time-Series AI Agent with Exploratory Execution Learning Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:51:17.510960Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 79e2dde6-cc8e-438c-a421-f6f9a3441b3f · inbound

SurF: A Generative Model for Multivariate Irregular Time Series Forecasting cites this paper.

SurF: A Generative Model for Multivariate Irregular Time Series Forecasting Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 3

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Observation ab6310d4-9cee-4845-8d0f-f007e85ef4fb · 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 Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:20:24.963670Z

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GlucoFM: A Dual-Stream Foundation Model for Continuous Glucose Monitoring cites this paper.

GlucoFM: A Dual-Stream Foundation Model for Continuous Glucose Monitoring Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:02:50.252734Z

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Benchmarking Deep Time Series Models for Equity Portfolios cites this paper.

Benchmarking Deep Time Series Models for Equity Portfolios Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-06-27T15:41:00.591746Z

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Observation aa743716-ff40-47cc-841c-dacb036df744 · inbound

TimeRouter: Efficient and Adaptive Routing of Time-Series Foundation Models cites this paper.

TimeRouter: Efficient and Adaptive Routing of Time-Series Foundation Models Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 12

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Observation 18326e99-aa22-44e8-b7b0-032be2e29ccd · inbound

Time Series Analysis in Machine Learning cites this paper.

Time Series Analysis in Machine Learning Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 51

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Observation f7a88515-3a9c-47a8-bae0-29f120a2fe8c · inbound

Beyond Tokenization: Direct Timestep Embedding and Contrastive Alignment for Time-Series Question Answering cites this paper.

Beyond Tokenization: Direct Timestep Embedding and Contrastive Alignment for Time-Series Question Answering Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 9

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Observation f4b5dd28-f92a-4f05-84ef-6c8a0c085a25 · inbound

UC-Search: Risk-Aware Test-Time Search for Delayed Constrained Time-Series Control cites this paper.

UC-Search: Risk-Aware Test-Time Search for Delayed Constrained Time-Series Control Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 43

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Observation 06fa5440-2200-487d-a79f-b264736fa62f · inbound

UC-Search: Risk-Aware Test-Time Search for Delayed Constrained Time-Series Control cites this paper.

UC-Search: Risk-Aware Test-Time Search for Delayed Constrained Time-Series Control Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 8

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Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis cites this paper.

Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 104

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Observation 40c29aac-cc06-40a1-8191-826573590db1 · inbound

When Do Foundation Models Pay Off? A Break-Even Analysis of Pretrained Time Series Forecasters cites this paper.

When Do Foundation Models Pay Off? A Break-Even Analysis of Pretrained Time Series Forecasters Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 3

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VAIOM: Continuous-Input, Discrete-Output Decoder-Only Financial Sequence Modeling cites this paper.

VAIOM: Continuous-Input, Discrete-Output Decoder-Only Financial Sequence Modeling Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 14

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From Vector Autoregressions to AI-based Time Series Forecasting: A Review cites this paper.

From Vector Autoregressions to AI-based Time Series Forecasting: A Review Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 47

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A Benchmark for Electrical Load Forecasting Across Grid Levels: Time-Series Transformers Outperform Established Methods cites this paper.

A Benchmark for Electrical Load Forecasting Across Grid Levels: Time-Series Transformers Outperform Established Methods Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 41

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Residual-Guided Multi-Resolution Refinement of Foundation Models: A Case Study in Drought Forecasting cites this paper.

Residual-Guided Multi-Resolution Refinement of Foundation Models: A Case Study in Drought Forecasting Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 12

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Lightweight Wrappers for Adapting Time Series Foundation Models to Regional Drought Forecasting cites this paper.

Lightweight Wrappers for Adapting Time Series Foundation Models to Regional Drought Forecasting Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 28

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Observation fcb46b39-285c-48f6-9f50-6101975e2c3b · inbound

Trend strength predicts when generative foundation models win: a power-controlled benchmark, a mechanism, and an actionable selection rule cites this paper.

Trend strength predicts when generative foundation models win: a power-controlled benchmark, a mechanism, and an actionable selection rule Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 4

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Expert-Guided Forecast Editing for Time-Series Foundation Models cites this paper.

Expert-Guided Forecast Editing for Time-Series Foundation Models Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 4

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Observation f55f3edd-1638-4d78-9eaf-9850d687b13f · inbound

Hopformer: Homogeneity-Pursuit Transformer for Time Series Forecasting cites this paper.

Hopformer: Homogeneity-Pursuit Transformer for Time Series Forecasting Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 17

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LiFT-MPC: Language-in-the-Loop Feedback Tuning of Cost Previews for MPC cites this paper.

LiFT-MPC: Language-in-the-Loop Feedback Tuning of Cost Previews for MPC Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 5

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LLM as Forecasting Planner: Training-Free Text Conditioning for Time-Series Foundation Models cites this paper.

LLM as Forecasting Planner: Training-Free Text Conditioning for Time-Series Foundation Models Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 7

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Contextual Deconvolution for Variance-Stable Demand Sensing: Kernel-Modulated Operators in Promotional Retail cites this paper.

Contextual Deconvolution for Variance-Stable Demand Sensing: Kernel-Modulated Operators in Promotional Retail Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 59

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Observation bd514f7d-f30c-4d74-b7e2-1ac2bbf68cea · inbound

CENTILE: A Telemetry Foundation Model Evaluated by the Decisions It Drives cites this paper.

CENTILE: A Telemetry Foundation Model Evaluated by the Decisions It Drives Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 37

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