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---
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},
}
```