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Recent studies have shown the ability of large language models to perform a variety of tasks, including time series forecasting.
Distribution of residual autocorrelations in autoregressive-integrated moving average time series models
George EP Box and David A Pierce · 1970
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Dynamic time warping
Meinard Müller · 2007
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Anomaly detection using forecasting methods ARIMA and HWDS
Eduardo H.M. Pena et al · 2013
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LSTM-based encoder-decoder for multi-sensor anomaly detection
Pankaj Malhotra et al · 2016
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Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder · 2018
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Detecting spacecraft anomalies using LSTMs and nonparametric dynamic thresholding
Kyle Hundman et al · 2018
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A multimodal anomaly detector for robot-assisted feeding using an LSTM-based variational autoencoder
Daehyung Park et al · 2018
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Precision and recall for time series
Nesime Tatbul et al · 2018
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Language models are unsupervised multitask learners
Alec Radford et al · 2019
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Language models are few-shot learners
Tom Brown et al · 2020
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TadGAN: Time series anomaly detection using generative adversarial networks
Alexander Geiger et al · 2020
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Program synthesis with large language models, 2021
Jacob Austin et al · 2021
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Evaluating large language models trained on code, 2021
Mark Chen et al · 2021
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Sintel: A machine learning framework to extract insights from signals
Sarah Alnegheimish et al · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia et al · 2022
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Multitask prompted training enables zero-shot task generalization
Victor Sanh et al · 2022
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Tranad: deep transformer networks for anomaly detection in multivariate time series data
Shreshth Tuli et al · 2022
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Emergent abilities of large language models
Jason Wei et al · 2022
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery et al · 2023
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Forecastpfn: Synthetically-trained zero-shot forecasting
Samuel Dooley et al · 2023
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Large language models are zero-shot time series forecasters
Nate Gruver et al · 2023
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Mistral 7b, 2023
Albert Q. Jiang et al · 2023
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Generating images with multimodal language models
Jing Yu Koh et al · 2023
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Goat: Fine-tuned llama outperforms gpt-4 on arithmetic tasks, 2023
Tiedong Liu and Bryan Kian Hsiang Low · 2023
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AER: Auto-encoder with regression for time series anomaly detection
Lawrence Wong et al · 2022
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A systematic evaluation of large language models of code
Frank F Xu et al · 2022
Cited alongside, same era.
Anomaly Transformer: Time series anomaly detection with association discrepancy
Jiehui Xu et al · 2022
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Emergent and predictable memorization in large language models
Stella Biderman et al · 2023
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Speak, memory: An archaeology of books known to ChatGPT/GPT-4
Kent Chang et al · 2023
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Kashif Rasul et al · 2023
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Llama 2: Open foundation and fine-tuned chat models, 2023
Hugo Touvron et al · 2023
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Promptcast: A new prompt-based learning paradigm for time series forecasting, 2023
Hao Xue and Flora D. Salim · 2023
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Making the end-user a priority in benchmarking: Orionbench for unsupervised time series anomaly detection, 2024
Sarah Alnegheimish et al · 2024
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Chronos: Learning the language of time series
Abdul Fatir Ansari et al · 2024
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