STEP: Staged Parameter-Efficient Pre-training for Large Language Models (2024.acl-srw)
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| Challenge: | Existing methods for reducing computational costs during pre-training have been studied, but they often degrade performance under fair conditions. |
| Approach: | They propose a method that combines parameter-efficient tuning and staged training to reduce memory requirements while maintaining comparable performance. |
| Outcome: | The proposed method reduces memory requirements by 40.4% while maintaining comparable performance. |
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