---
library_name: transformers
tags: [language-model, spoken-language, catastrophic-forgetting]
---

# Model Description

This model is designed to address catastrophic forgetting in spoken language models during end-to-end training. It leverages innovative mitigation strategies to enhance model retention and performance over time. For more details, please refer to the paper by Hsiao et al. (2025) [here](https://arxiv.org/abs/2505.17496).

# Model Usage

To use this model, please check the [GitHub repository](https://github.com/chiyuanhsiao/ForgetSLM) for installation instructions, example code, and detailed usage guidelines. Ensure you have the required dependencies installed.


# Citation

If you use this model in your research or applications, please cite it as follows:

**APA:**
Hsiao, C.-Y., Lu, K.-H., Chang, K.-W., Yang, C.-K., Chen, W.-C., & Lee, H.-y. (2025). Analyzing Mitigation Strategies for Catastrophic Forgetting in End-to-End Training of Spoken Language Models. arXiv. https://arxiv.org/abs/2505.17496

**BibTeX:**
```
@misc{hsiao2025analyzingmitigationstrategiescatastrophic,
      title={Analyzing Mitigation Strategies for Catastrophic Forgetting in End-to-End Training of Spoken Language Models}, 
      author={Chi-Yuan Hsiao and Ke-Han Lu and Kai-Wei Chang and Chih-Kai Yang and Wei-Chih Chen and Hung-yi Lee},
      year={2025},
      eprint={2505.17496},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2505.17496}, 
}
```