RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models | Paper Citation Record

Observation aefd611d-8bd7-4905-a8e4-ca3ad6a345c3 · outbound

This paper cites Foundation models for time series analysis: A tutorial and survey.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Foundation models for time series analysis: A tutorial and survey

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.847037Z

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Observation acef9b67-6919-47ef-9757-0662eeefa68b · outbound

This paper cites Benchmarking foundation models for time-series forecasting: Zero-shot, few-shot, and full-shot evaluations.Computer Sciences & Mathematics Forum, 11(1):32, 2025.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Benchmarking foundation models for time-series forecasting: Zero-shot, few-shot, and full-shot evaluations.Computer Sciences & Mathematics Forum, 11(1):32, 2025

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.833392Z

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No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation add41a4f-d7d5-4cbc-8956-18db885dba91 · outbound

This paper cites OTexts, 2018.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models OTexts, 2018

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.771983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 6f557b59-9965-498d-a911-a4006955c035 · outbound

This paper cites Some recent advances in forecasting and control.Journal of the Royal Statistical Society, 17(2):91–109, 1968.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Some recent advances in forecasting and control.Journal of the Royal Statistical Society, 17(2):91–109, 1968

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.800577Z

Source-reported events for the cited work

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Observation 8ece6c94-88eb-4159-b28c-fecc7c2339d7 · outbound

This paper cites Long short-term memory.Neural Computation, 9(8):1735– 1780, 1997.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Long short-term memory.Neural Computation, 9(8):1735– 1780, 1997

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.837949Z

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No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation e7b06060-8b54-40c5-8599-433edc0bbf32 · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.584598Z

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Observation dd91377b-8482-4d87-b2d6-101a7cf4eed7 · outbound

This paper cites Think globally, act locally: A deep neural network approach to high-dimensional time series forecasting.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Think globally, act locally: A deep neural network approach to high-dimensional time series forecasting

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.833785Z

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Observation 0da3a268-3b64-4ec3-aee2-e70a82efffa7 · outbound

This paper cites NHITS: Neural hierarchical interpolation for time series forecasting.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models NHITS: Neural hierarchical interpolation for time series forecasting

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.820692Z

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Observation 0409cde5-359c-4ee6-8d72-6cb0824d8177 · outbound

This paper cites Temporal fusion transformers for inter- pretable multi-horizon time series forecasting.International Journal of Forecasting, 37(4):1748–1764, 2021.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Temporal fusion transformers for inter- pretable multi-horizon time series forecasting.International Journal of Forecasting, 37(4):1748–1764, 2021

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.822262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 546aa5b7-7ab3-4e22-9116-e158e3b6b3f2 · outbound

This paper cites Predictive maintenance in Industry 4.0: A survey of planning models and machine learning techniques.PeerJ Computer Science, 10:e2016, 2024.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Predictive maintenance in Industry 4.0: A survey of planning models and machine learning techniques.PeerJ Computer Science, 10:e2016, 2024

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.801731Z

Source-reported events for the cited work

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Observation b67777e1-0513-47a6-aa8c-1a28b4c62a33 · outbound

This paper cites Financial time series forecast- ing with deep learning: A systematic literature review: 2005–2019.Applied Soft Computing, 90:106181, 2020.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Financial time series forecast- ing with deep learning: A systematic literature review: 2005–2019.Applied Soft Computing, 90:106181, 2020

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.799802Z

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No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 13fa3775-3600-44b3-b548-79ec535436ab · outbound

This paper cites Time series prediction using deep learning methods in healthcare.ACM Transactions on Management Information Systems, 14(1):1–29, 2023.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Time series prediction using deep learning methods in healthcare.ACM Transactions on Management Information Systems, 14(1):1–29, 2023

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.835700Z

Source-reported events for the cited work

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Observation ba7ec1a8-860d-4647-8b49-9c206d442089 · outbound

This paper cites Springer, 2010.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Springer, 2010

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.784069Z

Source-reported events for the cited work

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Observation f4279ff4-9269-4697-98b1-25d196e75a95 · outbound

This paper cites Probabilistic electric load forecasting: A tutorial review.International Journal of Forecasting, 32(3):914–938, 2016.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Probabilistic electric load forecasting: A tutorial review.International Journal of Forecasting, 32(3):914–938, 2016

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.843311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation f62a19f8-9c5a-4544-8777-aa5f62ecff63 · outbound

This paper cites Diffusion convolutional recurrent neural network: Data-driven traffic forecasting.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Diffusion convolutional recurrent neural network: Data-driven traffic forecasting

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.824337Z

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No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 5de4d33e-723e-4c09-a0b5-18ff369b281c · outbound

This paper cites Chronos-2: From Univariate to Universal Forecasting.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Chronos-2: From Univariate to Universal Forecasting

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.577771Z

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Observation 8e5e1d4f-f648-457d-8e58-d46c65a80953 · outbound

This paper cites Timer-XL: Long-context transformers for unified time series forecasting.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Timer-XL: Long-context transformers for unified time series forecasting

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.936747Z

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Observation 5f35ee02-f631-414f-90d5-c5e8e298c58a · outbound

This paper cites Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.959418Z

Source-reported events for the cited work

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Observation d868ad20-4ea9-4f43-bc4b-6a1a703e7e57 · outbound

This paper cites itrans- former: Inverted transformers are effective for time series forecasting.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models itrans- former: Inverted transformers are effective for time series forecasting

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.925511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation bb060eba-de58-4c0a-b771-f9a6540ad6eb · outbound

This paper cites Empowering Time Series Analysis with Synthetic Data: A Survey and Outlook in the Era of Foundation Models.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Empowering Time Series Analysis with Synthetic Data: A Survey and Outlook in the Era of Foundation Models

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.632114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation da51c851-03ce-4403-a709-c9e41ac46508 · outbound

This paper cites Uncovering zero- shot generalization gaps in time-series foundation models using real-world videos.arXiv preprint arXiv:2509.26347, 2025.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Uncovering zero- shot generalization gaps in time-series foundation models using real-world videos.arXiv preprint arXiv:2509.26347, 2025

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-08T04:14:29.621152Z

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Observation c0fbb882-9a86-4d08-9c51-fd031a3a8051 · outbound

This paper cites Zero-Shot Time Series Forecasting with Covariates via In-Context Learning.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Zero-Shot Time Series Forecasting with Covariates via In-Context Learning

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.631594Z

Source-reported events for the cited work

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Observation 6b9efb0c-b950-4116-8cc1-19398b26fe99 · outbound

This paper cites This time is different: An observability perspective on time series foundation models.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models This time is different: An observability perspective on time series foundation models

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.916159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 6b0e6a9a-cc87-4b1f-a76d-b36a7bfb647e · outbound

This paper cites Only the Curve Shape Matters: Training Foundation Models for Zero-Shot Multivariate Time Series Forecasting through Next Curve Shape Prediction.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Only the Curve Shape Matters: Training Foundation Models for Zero-Shot Multivariate Time Series Forecasting through Next Curve Shape Prediction

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.610872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 02fa211a-0916-4ae6-a8b4-e2461ac86b72 · outbound

This paper cites B., M¨uller, S., Salinas, D., and Hutter, F.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models B., M¨uller, S., Salinas, D., and Hutter, F

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-07-08T04:14:29.608062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation d77718bb-10f7-4082-b5ab-3da8c338a571 · outbound

This paper cites Uni- fied training of universal time series forecasting transformers.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Uni- fied training of universal time series forecasting transformers

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:30.007264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 77e93f30-84f6-434b-84dd-0267dfea286a · outbound

This paper cites Generative adversarial networks in time series: A systematic literature review.ACM Computing Surveys, 55(10):1–31, 2023.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Generative adversarial networks in time series: A systematic literature review.ACM Computing Surveys, 55(10):1–31, 2023

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.898038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 7190d201-fb87-478e-9edc-48f1d679f7ba · outbound

This paper cites TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.623966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 18b47302-dfa0-42d6-a12e-97815aa4cace · outbound

This paper cites Diffusion-TS: Interpretable Diffusion for General Time Series Generation.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Diffusion-TS: Interpretable Diffusion for General Time Series Generation

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.634724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 3f89e52a-4182-4e33-867e-f995e99fc394 · outbound

This paper cites Chronos: Learning the Language of Time Series.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Chronos: Learning the Language of Time Series

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.620112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 7b7e506c-bf2e-4ca5-b264-22197f11c77c · outbound

This paper cites John Wiley & Sons, 2015.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models John Wiley & Sons, 2015

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.953824Z

Source-reported events for the cited work

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Observation bf145fed-e165-4c39-97fb-8465b74169b9 · outbound

This paper cites Hyndman, Anne B.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Hyndman, Anne B

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.973685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation f9226bf7-76d2-499a-b799-211b02e7bf7e · outbound

This paper cites A methodology for validating diversity in synthetic time series generation.MethodsX, 8:101459, 2021.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models A methodology for validating diversity in synthetic time series generation.MethodsX, 8:101459, 2021

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.980223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1fafac0b-939e-4d01-8f2f-b5aa2951ab49 · outbound

This paper cites fev-bench: A Realistic Benchmark for Time Series Forecasting.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models fev-bench: A Realistic Benchmark for Time Series Forecasting

Reference 34

Resolution: metadata mismatch; local_arxiv, observed 2026-07-08T04:14:29.634304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 60f0f5ba-a3fd-49eb-a6a6-2776c76e1001 · outbound

This paper cites GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.614299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 6eb679db-e9d7-43dd-a161-a377595271cd · outbound

This paper cites Monash Time Series Forecasting Archive.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Monash Time Series Forecasting Archive

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.622628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 59de71fd-88ca-42b1-a76d-9392313bc92a · outbound

This paper cites MO- MENT: A family of open time-series foundation models.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models MO- MENT: A family of open time-series foundation models

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.975383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 466f0711-8d9d-4d03-ab22-70b78a2075a2 · outbound

This paper cites A decoder-only foundation model for time-series forecasting.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models A decoder-only foundation model for time-series forecasting

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.887855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 595ce791-2395-417f-beb4-8f80a3fe4249 · outbound

This paper cites Appliance consumption signature database and recognition test protocols.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Appliance consumption signature database and recognition test protocols

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.951592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 59985441-6dc9-4b3b-9276-2d58ca6fa4d6 · outbound

This paper cites Fast and accurate time series classification with WEASEL.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Fast and accurate time series classification with WEASEL

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.903141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation bbdfed29-132c-4c3a-b858-a1b15dff90e0 · outbound

This paper cites Time-MoE: Billion-scale time series foundation models with mixture of experts.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Time-MoE: Billion-scale time series foundation models with mixture of experts

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.995816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation c62cf408-2fce-4d78-a037-b3c1a22a2704 · outbound

This paper cites Meehl, Catherine A.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Meehl, Catherine A

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.947757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 84a67a78-6e89-41d0-ab38-7d74588dddcf · outbound

This paper cites Improving S&P stock prediction with time series stock similarity.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Improving S&P stock prediction with time series stock similarity

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.626781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 6f66001c-2928-4749-86da-1f6742fa96c2 · outbound

This paper cites CSTS: A Benchmark for the Discovery of Correlation Structures in Time Series Clustering.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models CSTS: A Benchmark for the Discovery of Correlation Structures in Time Series Clustering

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.637569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 9b6de39c-1b8a-42ee-b33e-c9b9efd6315d · outbound

This paper cites Appliances energy prediction.UCI Machine Learning Repository, 2017.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Appliances energy prediction.UCI Machine Learning Repository, 2017

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.939009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 5b0550a7-4879-49b6-b268-d8c7f1be5060 · outbound

This paper cites Aus- tralian electricity demand dataset.Zenodo, 2021.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Aus- tralian electricity demand dataset.Zenodo, 2021

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.921441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 952eb117-1481-427a-94c7-564b57265a84 · outbound

This paper cites Resource central: Understanding and predicting workloads for improved resource management in large cloud platforms.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Resource central: Understanding and predicting workloads for improved resource management in large cloud platforms

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.940728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation aecb863c-ccd6-40c8-96f7-a68ae0009667 · outbound

This paper cites Shape classifier based on generalized probabilistic descent method with hidden Markov descriptor.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Shape classifier based on generalized probabilistic descent method with hidden Markov descriptor

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.999309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation fedb4269-474a-459e-ad9f-eca8bccf2a80 · outbound

This paper cites The building data genome project 2, energy meter data from the ASHRAE great energy predictor III competition.Scientific Data, 7(368), 2020.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models The building data genome project 2, energy meter data from the ASHRAE great energy predictor III competition.Scientific Data, 7(368), 2020

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.978305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8635f070-43e5-4875-9213-a5d3146d8342 · outbound

This paper cites ClimateLearn: Benchmarking machine learning for weather and climate modeling.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models ClimateLearn: Benchmarking machine learning for weather and climate modeling

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.949789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8e59e64b-3c43-4dd6-a7fe-57bfdb043a9b · outbound

This paper cites Hasell, E.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Hasell, E

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.933160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1823fa87-5c4b-47b7-9502-1f26eea2a59c · outbound

This paper cites Mathieu, H.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Mathieu, H

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.967548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1f557406-a83a-4925-bdfc-3ba93786004f · outbound

This paper cites Gas sensor array temperature modulation.UCI Machine Learning Repository, 2018.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Gas sensor array temperature modulation.UCI Machine Learning Repository, 2018

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.979115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation d54d933c-c9b6-4051-9f7a-ef5e84efa0a0 · outbound

This paper cites COVID-19 deaths dataset.Zenodo, 2020.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models COVID-19 deaths dataset.Zenodo, 2020

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.901370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 402fcd8e-2a86-4588-82e5-492a6e9311b0 · outbound

This paper cites COVID-19 mobility dataset (with missing values).Zenodo, 2021.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models COVID-19 mobility dataset (with missing values).Zenodo, 2021

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.958864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1d58fe99-8746-4384-a849-40a28115e679 · outbound

This paper cites KDD cup dataset (with missing values).Zenodo, 2020.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models KDD cup dataset (with missing values).Zenodo, 2020

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.964157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 57c351ff-b85d-4353-ac21-247fcfd9ba90 · outbound

This paper cites Oikolab weather dataset.Zenodo, 2021.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Oikolab weather dataset.Zenodo, 2021

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:30.009079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 250d6912-e8a4-41fe-a256-ffa96bf4519f · outbound

This paper cites Krilova, I.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Krilova, I

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.991956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 823cda1e-3370-40b7-b322-d158d9ea7fd5 · outbound

This paper cites PM2.5 data of five Chinese cities.UCI Machine Learning Repository, 2016.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models PM2.5 data of five Chinese cities.UCI Machine Learning Repository, 2016

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.917895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 54f20e18-263c-49a8-b811-c4dae1361ec5 · outbound

This paper cites Abdulaal and T.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Abdulaal and T

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.914450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8ccb881d-eccf-44fb-9de3-e80f98455f36 · outbound

This paper cites Abdulaal, Z.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Abdulaal, Z

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:30.002965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 11724098-0caa-4fd0-88af-2c490f49e777 · outbound

This paper cites BuildingsBench: A large-scale dataset of 900k buildings and benchmark for short-term load forecasting.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models BuildingsBench: A large-scale dataset of 900k buildings and benchmark for short-term load forecasting

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.985269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1a00b81b-85ce-4d39-aeb7-9d7bb7c1db38 · outbound

This paper cites Sub- seasonalClimateUSA: A dataset for subseasonal forecasting and benchmarking.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Sub- seasonalClimateUSA: A dataset for subseasonal forecasting and benchmarking

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.923491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation cbd27eec-3ec7-4335-aae2-af683986dfc0 · outbound

This paper cites Grundy, Alison E.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Grundy, Alison E

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.927137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 7bdba23f-31e4-46a3-878f-1579a3d22d39 · outbound

This paper cites Temperature rain dataset without missing values.Zenodo, 2021.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Temperature rain dataset without missing values.Zenodo, 2021

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:30.001343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation a8162acd-a1fc-4928-b7d8-febe8b7f4122 · outbound

This paper cites Yap, Matthew Amos, and Flora D.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Yap, Matthew Amos, and Flora D

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.960724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 6ed42de8-ccd7-4e7a-8982-6a3b975fc99d · outbound

This paper cites Dueben, Sebastian Scher, Jonathan A.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Dueben, Sebastian Scher, Jonathan A

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.983437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8828adfe-c972-4b93-9711-b71a376465f8 · outbound

This paper cites BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation

Reference 68

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.629562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation e5d7b360-3b80-4a6b-b3ac-0d087aed629a · outbound

This paper cites Multivariate gait data.UCI Machine Learning Reposi- tory, 2016.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Multivariate gait data.UCI Machine Learning Reposi- tory, 2016

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.972122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 91a0e6e6-8aa6-4f5a-ba0f-ad4f8acd8aec · outbound

This paper cites HAR70+.UCI Machine Learning Repository, 2023.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models HAR70+.UCI Machine Learning Repository, 2023

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:30.012153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation b7614f83-7e25-469b-ad81-af59ed9713ad · outbound

This paper cites Weather dataset.Zenodo, 2020.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Weather dataset.Zenodo, 2020

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.948311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 61e45c49-800c-4fb2-8a09-160da44da835 · outbound

This paper cites Beaver, Raymond C.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Beaver, Raymond C

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.980877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation a77601bb-d770-4383-afad-815c76deea26 · outbound

This paper cites an unresolved cited work.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-07-08T04:14:29.990296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 7f7ca8c2-8ed3-4d46-bece-60e35bf78de2 · outbound

This paper cites Gas sensor array under dynamic gas mixtures.UCI Machine Learning Repository, 2015.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Gas sensor array under dynamic gas mixtures.UCI Machine Learning Repository, 2015

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.997591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 4176e6d4-8712-4b8a-922e-3d455d0f2a00 · outbound

This paper cites Heterogeneity activity recognition.UCI Machine Learning Repository, 2015.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Heterogeneity activity recognition.UCI Machine Learning Repository, 2015

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.957148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation dbc89a0d-4d06-4363-894d-cde309207769 · outbound

This paper cites A three-year building operational performance dataset for informing energy efficiency.Dryad, 2022.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models A three-year building operational performance dataset for informing energy efficiency.Dryad, 2022

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.928627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 4ca8ed26-18b5-4a97-a796-d3dbe8803987 · outbound

This paper cites Hungarian chickenpox cases.UCI Machine Learning Repository, 2021.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Hungarian chickenpox cases.UCI Machine Learning Repository, 2021

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.976275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 60e26f5c-60ae-42cf-b983-3ddc00ae1721 · outbound

This paper cites Occupancy detection.UCI Machine Learning Repository, 2016.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Occupancy detection.UCI Machine Learning Repository, 2016

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.966818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 442ce963-db3a-4bd5-ba4c-0a41e28560e1 · outbound

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

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Informer: Beyond efficient Transformer for long sequence time-series forecasting

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.977175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation db0aee6d-2df3-4c1d-a3b8-e1ca96b81313 · outbound

This paper cites Price graphs: Utilizing the structural information of financial time series for stock prediction.Information Sciences, 588:405–424, 2022.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Price graphs: Utilizing the structural information of financial time series for stock prediction.Information Sciences, 588:405–424, 2022

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:30.005430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 55b39fb9-ad3d-47c8-9e47-0b77094cf2d5 · outbound

This paper cites Barsocchi, A.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Barsocchi, A

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.981825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 60f3c7b2-8117-4182-8f08-41cd2376cf2f · outbound

This paper cites Benchmarks and Custom Package for Energy Forecasting.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Benchmarks and Custom Package for Energy Forecasting

Reference 82

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:14:29.607992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 7dd60e3a-d8e8-4634-a352-a9096feb95e9 · outbound

This paper cites G ¨orich und Weiersh¨auser, 2006.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models G ¨orich und Weiersh¨auser, 2006

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.969299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation d2c8c97d-acc9-4faf-831b-24f3b9041220 · outbound

This paper cites Electricity load Diagrams(20112014).UCI Machine Learning Repository, 2015.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Electricity load Diagrams(20112014).UCI Machine Learning Repository, 2015

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.931083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1420badd-7581-48a7-baf5-d0cc97ecfe89 · outbound

This paper cites Room occupancy estimation.UCI Machine Learning Reposi- tory, 2018.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Room occupancy estimation.UCI Machine Learning Reposi- tory, 2018

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.942724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8f3a4a32-666d-45dd-8384-038f6c659083 · outbound

This paper cites Barbara, Timothy R.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Barbara, Timothy R

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.974453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 5655792e-68d4-4501-80de-d862fffedaef · outbound

This paper cites Electricity hourly dataset.Zenodo, 2020.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Electricity hourly dataset.Zenodo, 2020

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.953638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 7076e3c1-21d7-4c40-b579-45c81098fe3e · outbound

This paper cites an unresolved cited work.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-07-08T04:14:29.903299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation fd5c5180-8e48-4c87-adc4-6b22be88c2cc · outbound

This paper cites Automixer for improved multivariate time-series forecasting on business and IT observability data.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Automixer for improved multivariate time-series forecasting on business and IT observability data

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.971157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 41539c1a-400b-4166-bd7c-5417834365c2 · outbound

This paper cites Robust anomaly detection for multivariate time series through stochastic recurrent neural network.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Robust anomaly detection for multivariate time series through stochastic recurrent neural network

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.965883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation fad348e4-a158-4214-8d96-f92069fe3853 · outbound

This paper cites Individual household electric power consumption.UCI Machine Learning Repository, 2006.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Individual household electric power consumption.UCI Machine Learning Repository, 2006

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.925325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 01f972b9-7378-407a-a796-400ca23736da · outbound

This paper cites Mel- bourne pedestrian counts dataset.Zenodo, 2020.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Mel- bourne pedestrian counts dataset.Zenodo, 2020

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.994123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 5ecb45cb-e3c6-4247-a1b4-bd241f0d1ba5 · outbound

This paper cites Deep learning architecture for short- term passenger flow forecasting in urban rail transit.IEEE Transactions on Intelligent Transportation Systems, 22(11):7004–7014, 2020.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Deep learning architecture for short- term passenger flow forecasting in urban rail transit.IEEE Transactions on Intelligent Transportation Systems, 22(11):7004–7014, 2020

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.961414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation abe16b91-0294-4a71-acb8-7fe26f491c21 · outbound

This paper cites Functional relation field: A model-agnostic framework for multivariate time series forecasting.Artificial Intelligence, 334, 2024.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Functional relation field: A model-agnostic framework for multivariate time series forecasting.Artificial Intelligence, 334, 2024

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.987028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation d9be0760-dbb5-467b-8352-2f65bba8df15 · outbound

This paper cites Lon- don smart meters dataset (with missing values).Zenodo, 2020.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Lon- don smart meters dataset (with missing values).Zenodo, 2020

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.962387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1e4999df-cb02-48b6-a989-0fb320964867 · outbound

This paper cites When will you arrive? Estimating travel time based on deep neural networks.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models When will you arrive? Estimating travel time based on deep neural networks

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.919822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 3c149e64-4c56-4bad-820a-f80be38eed82 · outbound

This paper cites Clegg, Andrea Cavallaro, and Hamed Haddadi.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Clegg, Andrea Cavallaro, and Hamed Haddadi

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:30.010617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation a76aed73-2796-436b-a0ad-68746f9c10bf · outbound

This paper cites LibCity: An open library for traffic prediction.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models LibCity: An open library for traffic prediction

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.972866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 5de77c9b-5b88-46f1-897f-87e48a4a1c66 · outbound

This paper cites Electric motor temperature.Kaggle, 2021.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models Electric motor temperature.Kaggle, 2021

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:29.988777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 4f15b804-8111-43ed-bd8e-c44875247559 · outbound

This paper cites A spatio-temporal attention-based spot-forecasting framework for urban traffic prediction.Applied Soft Computing, 96, 2020.

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models A spatio-temporal attention-based spot-forecasting framework for urban traffic prediction.Applied Soft Computing, 96, 2020

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T04:14:30.014651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

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