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# TriP-LLM
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).
## Model Description
- **Name**: TriP-LLM
- **Task**: Time-Series Anomaly Detection
- **Framework**: PyTorch
- **Repository**: [GitHub – YYZStart/TriP-LLM](https://github.com/YYZStart/TriP-LLM)
## Usage
Please refer to our [GitHub repository](https://github.com/YYZStart/TriP-LLM)
for model definitions, training code, and usage examples.
## 📎 Citation
If you find this repository useful for your research, please cite our paper:
```bibtex
@misc{TriPLLM,
title={TriP-LLM: A Tri-Branch Patch-wise Large Language Model Framework for Time-Series Anomaly Detection},
author={Yuan-Cheng Yu and Yen-Chieh Ouyang and Chun-An Lin},
journal={IEEE Access},
year={2025},
pages={168643-168653}
}
``` |