Forward Knows Efficient Backward Path: Saliency-Guided Memory-Efficient Fine-tuning of Large Language Models (2025.acl-long)
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| Challenge: | a number of fine-tuning approaches are available to improve performance of large language models. |
| Approach: | They propose a memory-efficient method to minimize memory associated with cached intermediate activations. |
| Outcome: | The proposed method minimizes memory associated with cached intermediate activations while preserving accuracy. |
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