diff --git a/README.md b/README.md
index fb77cedd..c11fe903 100644
--- a/README.md
+++ b/README.md
@@ -113,47 +113,47 @@ The task types are abbreviated as follows:
**`ANOD`**: Anomaly Detection.
The paper references and links are all listed at the bottom of this file.
-| **Type** | **Algo** | **IMPU** | **FORE** | **CLAS** | **CLUS** | **ANOD** | **Year - Venue** |
-|:--------------|:----------------------------|:--------:|:--------:|:--------:|:--------:|:--------:|:-------------------|
-| LLM | Gungnir 🚀 [^36] | ✅ | ✅ | ✅ | ✅ | ✅ | `Later in 2024` |
-| Neural Net | ImputeFormer🧑🔧[^34] | ✅ | | | | | `2024 - KDD` |
-| Neural Net | iTransformer🧑🔧[^24] | ✅ | | | | | `2024 - ICLR` |
-| Neural Net | SAITS[^1] | ✅ | | | | | `2023 - ESWA` |
-| Neural Net | FreTS🧑🔧[^23] | ✅ | | | | | `2023 - NeurIPS` |
-| Neural Net | Koopa🧑🔧[^29] | ✅ | | | | | `2023 - NeurIPS` |
-| Neural Net | Crossformer🧑🔧[^16] | ✅ | | | | | `2023 - ICLR` |
-| Neural Net | TimesNet[^14] | ✅ | | | | | `2023 - ICLR` |
-| Neural Net | PatchTST🧑🔧[^18] | ✅ | | | | | `2023 - ICLR` |
-| Neural Net | ETSformer🧑🔧[^19] | ✅ | | | | | `2023 - ICLR` |
-| Neural Net | MICN🧑🔧[^27] | ✅ | | | | | `2023 - ICLR` |
-| Neural Net | DLinear🧑🔧[^17] | ✅ | | | | | `2023 - AAAI` |
-| Neural Net | TiDE🧑🔧[^28] | ✅ | | | | | `2023 - TMLR` |
-| Neural Net | SCINet🧑🔧[^30] | ✅ | | | | | `2022 - NeurIPS` |
-| Neural Net | Nonstationary Tr.🧑🔧[^25] | ✅ | | | | | `2022 - NeurIPS` |
-| Neural Net | FiLM🧑🔧[^22] | ✅ | | | | | `2022 - NeurIPS` |
-| Neural Net | RevIN_SCINet🧑🔧[^31] | ✅ | | | | | `2022 - ICLR` |
-| Neural Net | Pyraformer🧑🔧[^26] | ✅ | | | | | `2022 - ICLR` |
-| Neural Net | Raindrop[^5] | | | ✅ | | | `2022 - ICLR` |
-| Neural Net | FEDformer🧑🔧[^20] | ✅ | | | | | `2022 - ICML` |
-| Neural Net | Autoformer🧑🔧[^15] | ✅ | | | | | `2021 - NeurIPS` |
-| Neural Net | CSDI[^12] | ✅ | ✅ | | | | `2021 - NeurIPS` |
-| Neural Net | Informer🧑🔧[^21] | ✅ | | | | | `2021 - AAAI` |
-| Neural Net | US-GAN[^10] | ✅ | | | | | `2021 - AAAI` |
-| Neural Net | CRLI[^6] | | | | ✅ | | `2021 - AAAI` |
-| Probabilistic | BTTF[^8] | | ✅ | | | | `2021 - TPAMI` |
-| Neural Net | StemGNN🧑🔧[^33] | ✅ | | | | | `2020 - NeurIPS` |
-| Neural Net | Reformer🧑🔧[^32] | ✅ | | | | | `2020 - ICLR` |
-| Neural Net | GP-VAE[^11] | ✅ | | | | | `2020 - AISTATS` |
-| Neural Net | VaDER[^7] | | | | ✅ | | `2019 - GigaSci.` |
-| Neural Net | M-RNN[^9] | ✅ | | | | | `2019 - TBME` |
-| Neural Net | BRITS[^3] | ✅ | | ✅ | | | `2018 - NeurIPS` |
-| Neural Net | GRU-D[^4] | ✅ | | ✅ | | | `2018 - Sci. Rep.` |
-| Neural Net | TCN🧑🔧[^35] | ✅ | | | | | `2018 - arXiv` |
-| Neural Net | Transformer🧑🔧[^2] | ✅ | | | | | `2017 - NeurIPS` |
-| Naive | Lerp | ✅ | | | | | |
-| Naive | LOCF/NOCB | ✅ | | | | | |
-| Naive | Mean | ✅ | | | | | |
-| Naive | Median | ✅ | | | | | |
+| **Type** | **Algo** | **IMPU** | **FORE** | **CLAS** | **CLUS** | **ANOD** | **Year - Venue** |
+|:--------------|:---------------------------------------------------------------------------------------------------------------------------------|:--------:|:--------:|:--------:|:--------:|:--------:|:-------------------|
+| LLM | Time-Series.AI [^36] | ✅ | ✅ | ✅ | ✅ | ✅ | `Later in 2024` |
+| Neural Net | ImputeFormer🧑🔧[^34] | ✅ | | | | | `2024 - KDD` |
+| Neural Net | iTransformer🧑🔧[^24] | ✅ | | | | | `2024 - ICLR` |
+| Neural Net | SAITS[^1] | ✅ | | | | | `2023 - ESWA` |
+| Neural Net | FreTS🧑🔧[^23] | ✅ | | | | | `2023 - NeurIPS` |
+| Neural Net | Koopa🧑🔧[^29] | ✅ | | | | | `2023 - NeurIPS` |
+| Neural Net | Crossformer🧑🔧[^16] | ✅ | | | | | `2023 - ICLR` |
+| Neural Net | TimesNet[^14] | ✅ | | | | | `2023 - ICLR` |
+| Neural Net | PatchTST🧑🔧[^18] | ✅ | | | | | `2023 - ICLR` |
+| Neural Net | ETSformer🧑🔧[^19] | ✅ | | | | | `2023 - ICLR` |
+| Neural Net | MICN🧑🔧[^27] | ✅ | | | | | `2023 - ICLR` |
+| Neural Net | DLinear🧑🔧[^17] | ✅ | | | | | `2023 - AAAI` |
+| Neural Net | TiDE🧑🔧[^28] | ✅ | | | | | `2023 - TMLR` |
+| Neural Net | SCINet🧑🔧[^30] | ✅ | | | | | `2022 - NeurIPS` |
+| Neural Net | Nonstationary Tr.🧑🔧[^25] | ✅ | | | | | `2022 - NeurIPS` |
+| Neural Net | FiLM🧑🔧[^22] | ✅ | | | | | `2022 - NeurIPS` |
+| Neural Net | RevIN_SCINet🧑🔧[^31] | ✅ | | | | | `2022 - ICLR` |
+| Neural Net | Pyraformer🧑🔧[^26] | ✅ | | | | | `2022 - ICLR` |
+| Neural Net | Raindrop[^5] | | | ✅ | | | `2022 - ICLR` |
+| Neural Net | FEDformer🧑🔧[^20] | ✅ | | | | | `2022 - ICML` |
+| Neural Net | Autoformer🧑🔧[^15] | ✅ | | | | | `2021 - NeurIPS` |
+| Neural Net | CSDI[^12] | ✅ | ✅ | | | | `2021 - NeurIPS` |
+| Neural Net | Informer🧑🔧[^21] | ✅ | | | | | `2021 - AAAI` |
+| Neural Net | US-GAN[^10] | ✅ | | | | | `2021 - AAAI` |
+| Neural Net | CRLI[^6] | | | | ✅ | | `2021 - AAAI` |
+| Probabilistic | BTTF[^8] | | ✅ | | | | `2021 - TPAMI` |
+| Neural Net | StemGNN🧑🔧[^33] | ✅ | | | | | `2020 - NeurIPS` |
+| Neural Net | Reformer🧑🔧[^32] | ✅ | | | | | `2020 - ICLR` |
+| Neural Net | GP-VAE[^11] | ✅ | | | | | `2020 - AISTATS` |
+| Neural Net | VaDER[^7] | | | | ✅ | | `2019 - GigaSci.` |
+| Neural Net | M-RNN[^9] | ✅ | | | | | `2019 - TBME` |
+| Neural Net | BRITS[^3] | ✅ | | ✅ | | | `2018 - NeurIPS` |
+| Neural Net | GRU-D[^4] | ✅ | | ✅ | | | `2018 - Sci. Rep.` |
+| Neural Net | TCN🧑🔧[^35] | ✅ | | | | | `2018 - arXiv` |
+| Neural Net | Transformer🧑🔧[^2] | ✅ | | | | | `2017 - NeurIPS` |
+| Naive | Lerp | ✅ | | | | | |
+| Naive | LOCF/NOCB | ✅ | | | | | |
+| Naive | Mean | ✅ | | | | | |
+| Naive | Median | ✅ | | | | | |
💯 Contribute your model right now to increase your research impact! PyPOTS downloads are increasing rapidly (**[300K+ in total and 1K+ daily on PyPI so far](https://www.pepy.tech/projects/pypots)**),
and your work will be widely used and cited by the community.
@@ -394,3 +394,4 @@ PyPOTS community is open, transparent, and surely friendly. Let's work together
[^35]: Bai, S., Kolter, J. Z., & Koltun, V. (2018). [An empirical evaluation of generic convolutional and recurrent networks for sequence modeling](https://arxiv.org/abs/1803.01271). *arXiv 2018*.
[^36]: Project Gungnir, the world 1st LLM for time-series multitask modeling, will meet you soon. 🚀 Missing values and variable lengths in your datasets?
Hard to perform multitask learning with your time series? Not problems no longer. We'll open application for public beta test recently ;-) Follow us, and stay tuned!
+ Time-Series.AI
diff --git a/README_zh.md b/README_zh.md
index b04dd28d..e0c6eb08 100644
--- a/README_zh.md
+++ b/README_zh.md
@@ -99,47 +99,47 @@ PyPOTS当前支持多变量POTS数据的插补,预测,分类,聚类以及
所以这些模型的输入中不能带有缺失值,无法接受POTS数据作为输入,更加不是插补算法。
**为了使上述模型能够适用于POTS数据,我们采用了与[SAITS论文](https://arxiv.org/pdf/2202.08516)[^1]中相同的embedding策略和训练方法(ORT+MIT)对它们进行改进**。
-| **类型** | **算法** | **插补** | **预测** | **分类** | **聚类** | **异常检测** | **年份 - 刊物** |
-|:--------------|:----------------------------|:------:|:------:|:------:|:------:|:--------:|:-------------------|
-| LLM | Gungnir 🚀 [^36] | ✅ | ✅ | ✅ | ✅ | ✅ | `Later in 2024` |
-| Neural Net | ImputeFormer🧑🔧[^34] | ✅ | | | | | `2024 - KDD` |
-| Neural Net | iTransformer🧑🔧[^24] | ✅ | | | | | `2024 - ICLR` |
-| Neural Net | SAITS[^1] | ✅ | | | | | `2023 - ESWA` |
-| Neural Net | FreTS🧑🔧[^23] | ✅ | | | | | `2023 - NeurIPS` |
-| Neural Net | Koopa🧑🔧[^29] | ✅ | | | | | `2023 - NeurIPS` |
-| Neural Net | Crossformer🧑🔧[^16] | ✅ | | | | | `2023 - ICLR` |
-| Neural Net | TimesNet[^14] | ✅ | | | | | `2023 - ICLR` |
-| Neural Net | PatchTST🧑🔧[^18] | ✅ | | | | | `2023 - ICLR` |
-| Neural Net | ETSformer🧑🔧[^19] | ✅ | | | | | `2023 - ICLR` |
-| Neural Net | MICN🧑🔧[^27] | ✅ | | | | | `2023 - ICLR` |
-| Neural Net | DLinear🧑🔧[^17] | ✅ | | | | | `2023 - AAAI` |
-| Neural Net | TiDE🧑🔧[^28] | ✅ | | | | | `2023 - TMLR` |
-| Neural Net | SCINet🧑🔧[^30] | ✅ | | | | | `2022 - NeurIPS` |
-| Neural Net | Nonstationary Tr.🧑🔧[^25] | ✅ | | | | | `2022 - NeurIPS` |
-| Neural Net | FiLM🧑🔧[^22] | ✅ | | | | | `2022 - NeurIPS` |
-| Neural Net | RevIN_SCINet🧑🔧[^31] | ✅ | | | | | `2022 - ICLR` |
-| Neural Net | Pyraformer🧑🔧[^26] | ✅ | | | | | `2022 - ICLR` |
-| Neural Net | Raindrop[^5] | | | ✅ | | | `2022 - ICLR` |
-| Neural Net | FEDformer🧑🔧[^20] | ✅ | | | | | `2022 - ICML` |
-| Neural Net | Autoformer🧑🔧[^15] | ✅ | | | | | `2021 - NeurIPS` |
-| Neural Net | CSDI[^12] | ✅ | ✅ | | | | `2021 - NeurIPS` |
-| Neural Net | Informer🧑🔧[^21] | ✅ | | | | | `2021 - AAAI` |
-| Neural Net | US-GAN[^10] | ✅ | | | | | `2021 - AAAI` |
-| Neural Net | CRLI[^6] | | | | ✅ | | `2021 - AAAI` |
-| Probabilistic | BTTF[^8] | | ✅ | | | | `2021 - TPAMI` |
-| Neural Net | StemGNN🧑🔧[^33] | ✅ | | | | | `2020 - NeurIPS` |
-| Neural Net | Reformer🧑🔧[^32] | ✅ | | | | | `2020 - ICLR` |
-| Neural Net | GP-VAE[^11] | ✅ | | | | | `2020 - AISTATS` |
-| Neural Net | VaDER[^7] | | | | ✅ | | `2019 - GigaSci.` |
-| Neural Net | M-RNN[^9] | ✅ | | | | | `2019 - TBME` |
-| Neural Net | BRITS[^3] | ✅ | | ✅ | | | `2018 - NeurIPS` |
-| Neural Net | GRU-D[^4] | ✅ | | ✅ | | | `2018 - Sci. Rep.` |
-| Neural Net | TCN🧑🔧[^35] | ✅ | | | | | `2018 - arXiv` |
-| Neural Net | Transformer🧑🔧[^2] | ✅ | | | | | `2017 - NeurIPS` |
-| Naive | Lerp | ✅ | | | | | |
-| Naive | LOCF/NOCB | ✅ | | | | | |
-| Naive | Mean | ✅ | | | | | |
-| Naive | Median | ✅ | | | | | |
+| **类型** | **算法** | **插补** | **预测** | **分类** | **聚类** | **异常检测** | **年份 - 刊物** |
+|:--------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------|:------:|:------:|:------:|:------:|:--------:|:-------------------|
+| LLM | Time-Series.AI [^36] | ✅ | ✅ | ✅ | ✅ | ✅ | `Later in 2024` |
+| Neural Net | ImputeFormer🧑🔧[^34] | ✅ | | | | | `2024 - KDD` |
+| Neural Net | iTransformer🧑🔧[^24] | ✅ | | | | | `2024 - ICLR` |
+| Neural Net | SAITS[^1] | ✅ | | | | | `2023 - ESWA` |
+| Neural Net | FreTS🧑🔧[^23] | ✅ | | | | | `2023 - NeurIPS` |
+| Neural Net | Koopa🧑🔧[^29] | ✅ | | | | | `2023 - NeurIPS` |
+| Neural Net | Crossformer🧑🔧[^16] | ✅ | | | | | `2023 - ICLR` |
+| Neural Net | TimesNet[^14] | ✅ | | | | | `2023 - ICLR` |
+| Neural Net | PatchTST🧑🔧[^18] | ✅ | | | | | `2023 - ICLR` |
+| Neural Net | ETSformer🧑🔧[^19] | ✅ | | | | | `2023 - ICLR` |
+| Neural Net | MICN🧑🔧[^27] | ✅ | | | | | `2023 - ICLR` |
+| Neural Net | DLinear🧑🔧[^17] | ✅ | | | | | `2023 - AAAI` |
+| Neural Net | TiDE🧑🔧[^28] | ✅ | | | | | `2023 - TMLR` |
+| Neural Net | SCINet🧑🔧[^30] | ✅ | | | | | `2022 - NeurIPS` |
+| Neural Net | Nonstationary Tr.🧑🔧[^25] | ✅ | | | | | `2022 - NeurIPS` |
+| Neural Net | FiLM🧑🔧[^22] | ✅ | | | | | `2022 - NeurIPS` |
+| Neural Net | RevIN_SCINet🧑🔧[^31] | ✅ | | | | | `2022 - ICLR` |
+| Neural Net | Pyraformer🧑🔧[^26] | ✅ | | | | | `2022 - ICLR` |
+| Neural Net | Raindrop[^5] | | | ✅ | | | `2022 - ICLR` |
+| Neural Net | FEDformer🧑🔧[^20] | ✅ | | | | | `2022 - ICML` |
+| Neural Net | Autoformer🧑🔧[^15] | ✅ | | | | | `2021 - NeurIPS` |
+| Neural Net | CSDI[^12] | ✅ | ✅ | | | | `2021 - NeurIPS` |
+| Neural Net | Informer🧑🔧[^21] | ✅ | | | | | `2021 - AAAI` |
+| Neural Net | US-GAN[^10] | ✅ | | | | | `2021 - AAAI` |
+| Neural Net | CRLI[^6] | | | | ✅ | | `2021 - AAAI` |
+| Probabilistic | BTTF[^8] | | ✅ | | | | `2021 - TPAMI` |
+| Neural Net | StemGNN🧑🔧[^33] | ✅ | | | | | `2020 - NeurIPS` |
+| Neural Net | Reformer🧑🔧[^32] | ✅ | | | | | `2020 - ICLR` |
+| Neural Net | GP-VAE[^11] | ✅ | | | | | `2020 - AISTATS` |
+| Neural Net | VaDER[^7] | | | | ✅ | | `2019 - GigaSci.` |
+| Neural Net | M-RNN[^9] | ✅ | | | | | `2019 - TBME` |
+| Neural Net | BRITS[^3] | ✅ | | ✅ | | | `2018 - NeurIPS` |
+| Neural Net | GRU-D[^4] | ✅ | | ✅ | | | `2018 - Sci. Rep.` |
+| Neural Net | TCN🧑🔧[^35] | ✅ | | | | | `2018 - arXiv` |
+| Neural Net | Transformer🧑🔧[^2] | ✅ | | | | | `2017 - NeurIPS` |
+| Naive | Lerp | ✅ | | | | | |
+| Naive | LOCF/NOCB | ✅ | | | | | |
+| Naive | Mean | ✅ | | | | | |
+| Naive | Median | ✅ | | | | | |
💯 现在贡献你的模型来增加你的研究影响力!PyPOTS的下载量正在迅速增长(**[目前PyPI上总共超过30万次且每日超1000的下载](https://www.pepy.tech/projects/pypots)**),
你的工作将被社区广泛使用和引用。请参阅[贡献指南](https://github.com/WenjieDu/PyPOTS/blob/main/README_zh.md#-%E8%B4%A1%E7%8C%AE%E5%A3%B0%E6%98%8E),了解如何将模型包含在PyPOTS中。
@@ -363,3 +363,4 @@ PyPOTS社区是一个开放、透明、友好的社区,让我们共同努力
[^34]: Nie, T., Qin, G., Mei, Y., & Sun, J. (2024). [ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation](https://arxiv.org/abs/2312.01728). *KDD 2024*.
[^35]: Bai, S., Kolter, J. Z., & Koltun, V. (2018). [An empirical evaluation of generic convolutional and recurrent networks for sequence modeling](https://arxiv.org/abs/1803.01271). *arXiv 2018*.
[^36]: Gungnir项目,世界上第一个时间序列多任务大模型,将很快与大家见面。🚀 数据集存在缺少值且样本长短不一?多任务建模场景困难?都不再是问题,让我们的大模型来帮你解决。我们将在近期开放公测申请 ;-) 关注我们,敬请期待!
+ Time-Series.AI