Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MOMENT: A Family of Open Time-series Foundation Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 58 inbound Pith citation observations for arXiv:2402.03885.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
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.
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External citation measurements
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Outbound references
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Pith citing papers
Observation 7a53f787-d66a-43ef-8d02-c99618f5e7a6 · inbound
Chronos: Learning the Language of Time Series cites this paper.
Chronos: Learning the Language of Time Series MOMENT: A Family of Open Time-series Foundation Models
Reference 33
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Observation 6bfe8d42-dc3c-4021-8f3d-ee8b9666e359 · inbound
TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis cites this paper.
TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis MOMENT: A Family of Open Time-series Foundation Models
Reference 11
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Observation 1970cbde-12ba-4f23-a488-ddac4fe26f9b · inbound
Sundial: A Family of Highly Capable Time Series Foundation Models cites this paper.
Sundial: A Family of Highly Capable Time Series Foundation Models MOMENT: A Family of Open Time-series Foundation Models
Reference 6
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Observation 057da507-5440-433c-a435-7733a6d55e9e · inbound
Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer cites this paper.
Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer MOMENT: A Family of Open Time-series Foundation Models
Reference 12
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Observation 3b5aec11-cfd0-4549-b884-8656a9799f14 · inbound
Time2Lang: Bridging Time-Series Foundation Models and Large Language Models for Health Sensing Beyond Prompting cites this paper.
Time2Lang: Bridging Time-Series Foundation Models and Large Language Models for Health Sensing Beyond Prompting MOMENT: A Family of Open Time-series Foundation Models
Reference 17
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Source-reported events for the cited work
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Observation cfa16717-6656-43d0-91f6-194c9d544c4e · inbound
Time to Embed: Unlocking Foundation Models for Time Series with Channel Descriptions cites this paper.
Time to Embed: Unlocking Foundation Models for Time Series with Channel Descriptions MOMENT: A Family of Open Time-series Foundation Models
Reference 27
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Source-reported events for the cited work
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Observation 683ee7c3-0140-4cc6-92d6-e9acce258bf4 · inbound
Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models cites this paper.
Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models MOMENT: A Family of Open Time-series Foundation Models
Reference 30
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Source-reported events for the cited work
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Observation 2d7ef63f-7286-4b97-8fe0-89003976937e · inbound
Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs cites this paper.
Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs MOMENT: A Family of Open Time-series Foundation Models
Reference 13
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Source-reported events for the cited work
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Observation 4d559046-14b6-46c3-98f3-bfc87ca7a9b1 · inbound
Delayformer: spatiotemporal transformation for predicting high-dimensional dynamics cites this paper.
Delayformer: spatiotemporal transformation for predicting high-dimensional dynamics MOMENT: A Family of Open Time-series Foundation Models
Reference 60
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Observation ff69d990-fea8-4712-a214-5936477b5c6f · 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 MOMENT: A Family of Open Time-series Foundation Models
Reference 29
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 71d08308-1006-449f-8cc3-f930f33cc915 · inbound
Escaping Plato's Cave: JAM for Aligning Independently Trained Vision and Language Models cites this paper.
Escaping Plato's Cave: JAM for Aligning Independently Trained Vision and Language Models MOMENT: A Family of Open Time-series Foundation Models
Reference 49
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Source-reported events for the cited work
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Observation b8cf1974-f6b9-458a-990f-da6e2d295c59 · inbound
Grounding Intelligence in Movement cites this paper.
Grounding Intelligence in Movement MOMENT: A Family of Open Time-series Foundation Models
Reference 30
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Source-reported events for the cited work
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Observation c3394481-3e8c-491b-bb72-44236b39135c · inbound
Scaling Transformers for Time Series Forecasting: Do Pretrained Large Models Outperform Small-Scale Alternatives? cites this paper.
Scaling Transformers for Time Series Forecasting: Do Pretrained Large Models Outperform Small-Scale Alternatives? MOMENT: A Family of Open Time-series Foundation Models
Reference 11
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Source-reported events for the cited work
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Observation 53a730d1-4ce5-4125-ad70-893c314796a8 · inbound
Causal Foundation Models: Disentangling Physics from Instrument Properties cites this paper.
Causal Foundation Models: Disentangling Physics from Instrument Properties MOMENT: A Family of Open Time-series Foundation Models
Reference 4
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Observation 82dfdd99-083d-4a00-b54e-8be3a3892ea4 · inbound
MoFE-Time: Mixture of Frequency Domain Experts for Time-Series Forecasting Models cites this paper.
MoFE-Time: Mixture of Frequency Domain Experts for Time-Series Forecasting Models MOMENT: A Family of Open Time-series Foundation Models
Reference 9
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Observation 19c89c08-3dea-4e58-b568-fad49162b233 · inbound
Towards Interpretable Time Series Foundation Models cites this paper.
Towards Interpretable Time Series Foundation Models MOMENT: A Family of Open Time-series Foundation Models
Reference 9
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Source-reported events for the cited work
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Observation 4d3697b6-780c-4db5-bd2f-0a729ce250a4 · inbound
Benchmarking Foundation Models with Multimodal Public Electronic Health Records cites this paper.
Benchmarking Foundation Models with Multimodal Public Electronic Health Records MOMENT: A Family of Open Time-series Foundation Models
Reference 27
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Source-reported events for the cited work
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Observation 5440a838-ce8c-4ba3-9d98-45f8493b3a76 · inbound
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 MOMENT: A Family of Open Time-series Foundation Models
Reference 10
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Source-reported events for the cited work
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Observation 27bf8389-e1e6-404b-a284-9ae33396a162 · inbound
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 MOMENT: A Family of Open Time-series Foundation Models
Reference 20
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Source-reported events for the cited work
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Observation 949d69ba-61ea-4af9-8db1-f3d7ca6ffd6e · inbound
CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams cites this paper.
CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams MOMENT: A Family of Open Time-series Foundation Models
Reference 6
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Source-reported events for the cited work
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Observation 3c7ce6ad-5008-41ff-8485-46ec99e2ac62 · inbound
WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting cites this paper.
WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting MOMENT: A Family of Open Time-series Foundation Models
Reference 21
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7fe332fe-87a7-4d94-a620-71e76ff24fad · inbound
Super-Linear: A Lightweight Pretrained Mixture of Linear Experts for Time Series Forecasting cites this paper.
Super-Linear: A Lightweight Pretrained Mixture of Linear Experts for Time Series Forecasting MOMENT: A Family of Open Time-series Foundation Models
Reference 12
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Source-reported events for the cited work
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Observation af99ebbb-3dce-4f29-b59b-51bc96facb2b · inbound
TS-Arena -- A Live Forecast Pre-Registration Platform cites this paper.
TS-Arena -- A Live Forecast Pre-Registration Platform MOMENT: A Family of Open Time-series Foundation Models
Reference 12
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Source-reported events for the cited work
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Observation f67d3f26-55f7-4c16-8076-bff2006aa847 · inbound
Lightweight Test-Time Adaptation for EMG-Based Gesture Recognition cites this paper.
Lightweight Test-Time Adaptation for EMG-Based Gesture Recognition MOMENT: A Family of Open Time-series Foundation Models
Reference 27
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Source-reported events for the cited work
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TimeSAE: Causal Sparse Decoding for Faithful Explanations of Black-Box Time Series Models cites this paper.
TimeSAE: Causal Sparse Decoding for Faithful Explanations of Black-Box Time Series Models MOMENT: A Family of Open Time-series Foundation Models
Reference 23
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Source-reported events for the cited work
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AnomSeer: Reinforcing Multimodal LLMs to Reason for Time-Series Anomaly Detection cites this paper.
AnomSeer: Reinforcing Multimodal LLMs to Reason for Time-Series Anomaly Detection MOMENT: A Family of Open Time-series Foundation Models
Reference 2012
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation def22747-0fa9-4d25-bc7c-5769f389ef66 · inbound
Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling cites this paper.
Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling MOMENT: A Family of Open Time-series Foundation Models
Reference 22
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Discrete Prototypical Memories for Federated Time Series Foundation Models cites this paper.
Discrete Prototypical Memories for Federated Time Series Foundation Models MOMENT: A Family of Open Time-series Foundation Models
Reference 10
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Source-reported events for the cited work
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Cross-Machine Anomaly Detection Leveraging Pre-trained Time-series Model cites this paper.
Cross-Machine Anomaly Detection Leveraging Pre-trained Time-series Model MOMENT: A Family of Open Time-series Foundation Models
Reference 33
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Source-reported events for the cited work
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LoRM: Learning the Language of Rotating Machinery for Self-Supervised Condition Monitoring cites this paper.
LoRM: Learning the Language of Rotating Machinery for Self-Supervised Condition Monitoring MOMENT: A Family of Open Time-series Foundation Models
Reference 19
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Observation 9899991e-64d4-4852-a342-b727d5feff50 · inbound
TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale cites this paper.
TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale MOMENT: A Family of Open Time-series Foundation Models
Reference 13
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TempusBench: An Evaluation Framework for Time-Series Forecasting cites this paper.
TempusBench: An Evaluation Framework for Time-Series Forecasting MOMENT: A Family of Open Time-series Foundation Models
Reference 6
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Adaptive Conformal Anomaly Detection with Time Series Foundation Models for Signal Monitoring cites this paper.
Adaptive Conformal Anomaly Detection with Time Series Foundation Models for Signal Monitoring MOMENT: A Family of Open Time-series Foundation Models
Reference 13
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GeoMind: An Agentic Workflow for Lithology Classification with Reasoned Tool Invocation cites this paper.
GeoMind: An Agentic Workflow for Lithology Classification with Reasoned Tool Invocation MOMENT: A Family of Open Time-series Foundation Models
Reference 14
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Empirical Assessment of Time-Series Foundation Models For Power System Forecasting Applications cites this paper.
Empirical Assessment of Time-Series Foundation Models For Power System Forecasting Applications MOMENT: A Family of Open Time-series Foundation Models
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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 MOMENT: A Family of Open Time-series Foundation Models
Reference 13
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GAFSV-Net: A Vision Framework for Online Signature Verification cites this paper.
GAFSV-Net: A Vision Framework for Online Signature Verification MOMENT: A Family of Open Time-series Foundation Models
Reference 5
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TimeClaw: A Time-Series AI Agent with Exploratory Execution Learning cites this paper.
TimeClaw: A Time-Series AI Agent with Exploratory Execution Learning MOMENT: A Family of Open Time-series Foundation Models
Reference 49
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NeuroAtlas: Benchmarking Foundation Models for Clinical EEG and Brain-Computer Interfaces cites this paper.
NeuroAtlas: Benchmarking Foundation Models for Clinical EEG and Brain-Computer Interfaces MOMENT: A Family of Open Time-series Foundation Models
Reference 24
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 8b6a347b-05cd-4401-afdd-338f25a01efc · inbound
Olivia: Harmonizing Time Series Foundation Models with Power Spectral Density cites this paper.
Olivia: Harmonizing Time Series Foundation Models with Power Spectral Density MOMENT: A Family of Open Time-series Foundation Models
Reference 4
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Source-reported events for the cited work
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Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs cites this paper.
Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs MOMENT: A Family of Open Time-series Foundation Models
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AION: Next-Generation Tasks and Practical Harness for Time Series cites this paper.
AION: Next-Generation Tasks and Practical Harness for Time Series MOMENT: A Family of Open Time-series Foundation Models
Reference 9
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e41681b8-fac3-4a2b-87d1-aa356dfef8fc · inbound
Why Do Time Series Models Need Long Context Windows? cites this paper.
Why Do Time Series Models Need Long Context Windows? MOMENT: A Family of Open Time-series Foundation Models
Reference 16
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 46bf2f04-dcb3-4b19-9961-8121ac609b62 · inbound
Combining Statistical Features and Deep Encodings for Rehearsal-Based Class-Incremental Time Series Classification cites this paper.
Combining Statistical Features and Deep Encodings for Rehearsal-Based Class-Incremental Time Series Classification MOMENT: A Family of Open Time-series Foundation Models
Reference 6
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f0c3df49-16e5-425b-a820-dfc73ff0ac4d · inbound
Towards Intrusion Detection Systems for RPL-based IoT Networks using Foundation Models cites this paper.
Towards Intrusion Detection Systems for RPL-based IoT Networks using Foundation Models MOMENT: A Family of Open Time-series Foundation Models
Reference 8
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation b403e40c-26da-40e1-b7ad-80fdbe3d5809 · inbound
TRACE: A Temporal Conditional Estimation for Multimodal Time Series Foundation Models cites this paper.
TRACE: A Temporal Conditional Estimation for Multimodal Time Series Foundation Models MOMENT: A Family of Open Time-series Foundation Models
Reference 7
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation ff771bf3-b11c-4d1c-bb38-4a64df1e5cbe · inbound
LakeFM: Toward a Foundation Model for Aquatic Ecosystems Using Irregular Multivariate Multi-depth Time Series Data cites this paper.
LakeFM: Toward a Foundation Model for Aquatic Ecosystems Using Irregular Multivariate Multi-depth Time Series Data MOMENT: A Family of Open Time-series Foundation Models
Reference 10
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 7357365b-54f2-4ac1-aa76-791a7a8979f7 · inbound
Are Time-Series Foundation Models Ready for E-Nose Data? An Empirical Assessment of Their Embeddings cites this paper.
Are Time-Series Foundation Models Ready for E-Nose Data? An Empirical Assessment of Their Embeddings MOMENT: A Family of Open Time-series Foundation Models
Reference 1
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d746886f-85c0-44c8-832b-26fd55b0bf98 · inbound
Beyond IID: How General Are Tabular Foundation Models, Really? cites this paper.
Beyond IID: How General Are Tabular Foundation Models, Really? MOMENT: A Family of Open Time-series Foundation Models
Reference 156
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 0b72c38d-048f-410f-93c2-766712c27fde · inbound
Relational and Sequential Conformal Inference for Energy Time Series over Graphs via Foundation Models cites this paper.
Relational and Sequential Conformal Inference for Energy Time Series over Graphs via Foundation Models MOMENT: A Family of Open Time-series Foundation Models
Reference 41
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d76ec23a-d820-4666-88fa-29e55b0b6872 · inbound
EVOTS: Evolutionary Transformer Search for Time Series Forecasting cites this paper.
EVOTS: Evolutionary Transformer Search for Time Series Forecasting MOMENT: A Family of Open Time-series Foundation Models
Reference 12
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 8662e74a-c8a4-4015-85dc-29304bd63839 · inbound
LeNEPA: No-Augmentation Next-Latent Prediction for Time-Series Representation Learning cites this paper.
LeNEPA: No-Augmentation Next-Latent Prediction for Time-Series Representation Learning MOMENT: A Family of Open Time-series Foundation Models
Reference 14
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 3a487d64-1977-4292-a030-3d9040fb3b35 · inbound
Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis cites this paper.
Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis MOMENT: A Family of Open Time-series Foundation Models
Reference 119
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 4b8f9102-ea46-4eea-8ca6-abbaa1b772e1 · inbound
Probabilistic Low-Voltage Peak Load Forecasting with Time Series Foundation Models Evaluated on Application-Oriented Metrics cites this paper.
Probabilistic Low-Voltage Peak Load Forecasting with Time Series Foundation Models Evaluated on Application-Oriented Metrics MOMENT: A Family of Open Time-series Foundation Models
Reference 33
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 781535af-56fc-491c-a310-cd2058bb3d00 · inbound
Learning Spatio-Temporal Foundation Models from Pure Synthetic Data cites this paper.
Learning Spatio-Temporal Foundation Models from Pure Synthetic Data MOMENT: A Family of Open Time-series Foundation Models
Reference 27
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 97865c67-605c-4732-b4cf-01f0f3de72e2 · 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 MOMENT: A Family of Open Time-series Foundation Models
Reference 5
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 81240bed-3c51-4376-a1d5-2e96ffb466af · inbound
LithoFormer: A Robust Framework for Stratigraphic Inference via Transformers cites this paper.
LithoFormer: A Robust Framework for Stratigraphic Inference via Transformers MOMENT: A Family of Open Time-series Foundation Models
Reference 11
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 69b3b5c3-ecd8-46b7-98e0-921d2c85c1e1 · inbound
DriveDNA: A Large-Scale Multimodal Naturalistic Driving Dataset and Benchmark for Driving Style Identification cites this paper.
DriveDNA: A Large-Scale Multimodal Naturalistic Driving Dataset and Benchmark for Driving Style Identification MOMENT: A Family of Open Time-series Foundation Models
Reference 14
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.