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# TriP-LLM
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This is the official checkpoints release for the **TriP-LLM**, a novel framework for unsupervised anomaly detection in multivariate time-series data using pretrained Large Language Models (LLMs).
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## Model Description
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- **Name**: TriP-LLM
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- **Task**: Time-Series Anomaly Detection
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- **Framework**: PyTorch
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- **Repository**: [GitHub – YYZStart/TriP-LLM](https://github.com/YYZStart/TriP-LLM)
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## Usage
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Please refer to our [GitHub repository](https://github.com/YYZStart/TriP-LLM)
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for model definitions, training code, and usage examples.
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## 📎 Citation
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If you find this repository useful for your research, please cite our paper:
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```bibtex
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@misc{TriPLLM,
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title={TriP-LLM: A Tri-Branch Patch-wise Large Language Model Framework for Time-Series Anomaly Detection},
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author={Yuan-Cheng Yu and Yen-Chieh Ouyang and Chun-An Lin},
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url={https://arxiv.org/abs/2508.00047},
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}
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```
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# TriP-LLM
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+
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This is the official checkpoints release for the **TriP-LLM**, a novel framework for unsupervised anomaly detection in multivariate time-series data using pretrained Large Language Models (LLMs).
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+
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+
## Model Description
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- **Name**: TriP-LLM
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- **Task**: Time-Series Anomaly Detection
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- **Framework**: PyTorch
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- **Repository**: [GitHub – YYZStart/TriP-LLM](https://github.com/YYZStart/TriP-LLM)
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## Usage
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Please refer to our [GitHub repository](https://github.com/YYZStart/TriP-LLM)
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for model definitions, training code, and usage examples.
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+
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## 📎 Citation
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If you find this repository useful for your research, please cite our paper:
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```bibtex
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@misc{TriPLLM,
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title={TriP-LLM: A Tri-Branch Patch-wise Large Language Model Framework for Time-Series Anomaly Detection},
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author={Yuan-Cheng Yu and Yen-Chieh Ouyang and Chun-An Lin},
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journal={IEEE Access},
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year={2025},
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pages={168643-168653}
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}
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```
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