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@@ -53,6 +53,7 @@ Till March 2024, the top three models for five different tasks are:
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See our latest paper [[TimesNet]](https://arxiv.org/abs/2210.02186) for the comprehensive benchmark. We will release a real-time updated online version soon.
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**Newly added baselines.** We will add them to the leaderboard after a comprehensive evaluation.
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- [x] **WPMixer** - WPMixer: Efficient Multi-Resolution Mixing for Long-Term Time Series Forecasting [[AAAI 2025]](https://arxiv.org/abs/2412.17176) [[Code]](https://github.com/thuml/Time-Series-Library/blob/main/models/WPMixer.py)
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- [x] **PAttn** - Are Language Models Actually Useful for Time Series Forecasting? [[NeurIPS 2024]](https://arxiv.org/pdf/2406.16964) [[Code]](https://github.com/thuml/Time-Series-Library/blob/main/models/PAttn.py)
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- [x] **Mamba** - Mamba: Linear-Time Sequence Modeling with Selective State Spaces [[arXiv 2023]](https://arxiv.org/abs/2312.00752) [[Code]](https://github.com/thuml/Time-Series-Library/blob/main/models/Mamba.py)
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- [x] **SegRNN** - SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting [[arXiv 2023]](https://arxiv.org/abs/2308.11200.pdf) [[Code]](https://github.com/thuml/Time-Series-Library/blob/main/models/SegRNN.py).

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