Papers by Yonglak Son
Not All Adapters Matter: Selective Adapter Freezing for Memory-Efficient Fine-Tuning of Language Models (2025.naacl-long)
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| Challenge: | Existing methods for fine-tuning pre-trained models impose substantial resource usage. |
| Approach: | They propose a parameter-efficient fine-tuning method that freezes adapters early to reduce resource usage while maintaining performance. |
| Outcome: | The proposed method reduces memory usage, computation amount, and training time by 42.85%, 34.59%, and 11.82% while maintaining performance. |