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Recent research has shown an increasing interest in utilizing pre-trained large language models (LLMs) for a variety of time series applications.
Robust estimation of a location parameter
Huber, P. J · 1992
Earlier work this paper cites.
Time series analysis: forecasting and control
Box, G. E., Jenkins, G. M., Reinsel, G. C., and Ljung, G. M · 2015
Earlier work this paper cites.
High-dimensional continuous control using generalized advantage estimation
Schulman, J., Moritz, P., Levine, S., Jordan, M., and Abbeel, P · 2015
Earlier work this paper cites.
A bias and variance analysis for multistep-ahead time series forecasting
Taieb, S. B. and Atiya, A. F · 2015
Earlier work this paper cites.
Decoupled weight decay regularization
Loshchilov, I · 2017
Earlier work this paper cites.
Proximal policy optimization algorithms
Schulman, J., Wolski, F., Dhariwal, P., Radford, A., and Klimov, O · 2017
Earlier work this paper cites.
Modeling long-and short-term temporal patterns with deep neural networks
Lai, G., Chang, W.-C., Yang, Y., and Liu, H · 2018
Earlier work this paper cites.
Improving language understanding by generative pre-training
Radford, A · 2018
Earlier work this paper cites.
A hybrid artificial neural network-gjr modeling approach to forecasting currency exchange rate volatility
Baffour, A. A., Feng, J., and Taylor, E. K · 2019
Earlier work this paper cites.
Pytorch: An imperative style, high-performance deep learning library
Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., et al · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I., et al · 2019
Earlier work this paper cites.
Spectral temporal graph neural network for multivariate time-series forecasting
Cao, D., Wang, Y., Duan, J., Zhang, C., Zhu, X., Huang, C., Tong, Y., Xu, B., Bai, J., Tong, J., et al · 2020
Earlier work this paper cites.
A primer on pretrained multilingual language models
Doddapaneni, S., Ramesh, G., Khapra, M. M., Kunchukuttan, A., and Kumar, P · 2021
Earlier work this paper cites.
Solar wind speed prediction with two-dimensional attention mechanism
Sun, Y., Xie, Z., Chen, Y., Huang, X., and Hu, Q · 2021
Earlier work this paper cites.
Informer: Beyond efficient transformer for long sequence time-series forecasting
Zhou, H., Zhang, S., Peng, J., Zhang, S., Li, J., Xiong, H., and Zhang, W · 2021
Cited alongside, same era.
A time series is worth 64 words: Long-term forecasting with transformers
Nie, Y., Nguyen, N. H., Sinthong, P., and Kalagnanam, J · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., et al · 2022
Cited alongside, same era.
Galactica: A large language model for science
Taylor, R., Kardas, M., Cucurull, G., Scialom, T., Hartshorn, A., Saravia, E., Poulton, A., Kerkez, V., and Stojnic, R · 2022
Cited alongside, same era.
Timesnet: Temporal 2d-variation modeling for general time series analysis
A decoder-only foundation model for time-series forecasting
Das, A., Kong, W., Sen, R., and Zhou, Y · 2024
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Ekambaram, V., Jati, A., Nguyen, N. H., Dayama, P., Reddy, C., Gifford, W. M., and Kalagnanam, J · 2024
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Large language models are zero-shot time series forecasters
Gruver, N., Finzi, M., Qiu, S., and Wilson, A. G · 2024
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Gpt4mts: Prompt-based large language model for multimodal time-series forecasting
Jia, F., Wang, K., Zheng, Y., Cao, D., and Liu, Y · 2024
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Unitime: A language-empowered unified model for cross-domain time series forecasting
Liu, X., Hu, J., Li, Y., Diao, S., Liang, Y., Hooi, B., and Zimmermann, R · 2024
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Wu, H., Hu, T., Liu, Y., Zhou, H., Wang, J., and Long, M · 2022
Cited alongside, same era.
Gqa: Training generalized multi-query transformer models from multi-head checkpoints
Ainslie, J., Lee-Thorp, J., de Jong, M., Zemlyanskiy, Y., Lebrón, F., and Sanghai, S · 2023
Cited alongside, same era.
Time-llm: Time series forecasting by reprogramming large language models
Jin, M., Wang, S., Ma, L., Chu, Z., Zhang, J. Y., Shi, X., Chen, P.-Y., Liang, Y., Li, Y.-F., Pan, S., et al · 2023
Cited alongside, same era.
itransformer: Inverted transformers are effective for time series forecasting
Liu, Y., Hu, T., Zhang, H., Wu, H., Wang, S., Ma, L., and Long, M · 2023
Cited alongside, same era.
Lag-llama: Towards foundation models for time series forecasting
Rasul, K., Ashok, A., Williams, A. R., Khorasani, A., Adamopoulos, G., Bhagwatkar, R., Biloš, M., Ghonia, H., Hassen, N., Schneider, A., et al · 2023
Cited alongside, same era.
Promptcast: A new prompt-based learning paradigm for time series forecasting
Xue, H. and Salim, F. D · 2023
Cited alongside, same era.
Are transformers effective for time series forecasting?
Zeng, A., Chen, M., Zhang, L., and Xu, Q · 2023
Cited alongside, same era.
One fits all: Power general time series analysis by pretrained lm
Zhou, T., Niu, P., Sun, L., Jin, R., et al · 2023
Cited alongside, same era.
Exploring progress in multivariate time series forecasting: Comprehensive benchmarking and heterogeneity analysis
Shao, Z., Wang, F., Xu, Y., Wei, W., Yu, C., Zhang, Z., Yao, D., Sun, T., Jin, G., Cao, X., et al · 2024
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Rose: Register assisted general time series forecasting with decomposed frequency learning
Wang, Y., Qiu, Y., Chen, P., Zhao, K., Shu, Y., Rao, Z., Pan, L., Yang, B., and Guo, C · 2024
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Yang, A., Yang, B., Hui, B., Zheng, B., Yu, B., Zhou, C., Li, C., Li, C., Liu, D., Huang, F., Dong, G., Wei, H., et al · 2024
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Ginar: An end-to-end multivariate time series forecasting model suitable for variable missing
Yu, C., Wang, F., Shao, Z., Qian, T., Zhang, Z., Wei, W., and Xu, Y · 2024
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Anygpt: Unified multimodal llm with discrete sequence modeling
Zhan, J., Dai, J., Ye, J., Zhou, Y., Zhang, D., Liu, Z., Zhang, X., Yuan, R., Zhang, G., Li, L., et al · 2024
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Notellm: A retrievable large language model for note recommendation
Zhang, C., Wu, S., Zhang, H., Xu, T., Gao, Y., Hu, Y., and Chen, E · 2024
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Hierarchical classification auxiliary network for time series forecasting
Sun, Y., Xie, Z., Chen, D., Eldele, E., and Hu, Q · 2025
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Mgsfformer: A multi-granularity spatiotemporal fusion transformer for air quality prediction
Yu, C., Wang, F., Wang, Y., Shao, Z., Sun, T., Yao, D., and Xu, Y · 2025
Closest in time.