Papers by Manxi Sun
Mixture of Diverse Size Experts (2024.emnlp-industry)
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| Challenge: | Recent large language models (LLMs) have shown superior performance in a variety of tasks due to the sub-linearly increasing computational costs. |
| Approach: | They propose a new MoE architecture with designed layers where experts have different sizes to mitigate this defect. |
| Outcome: | The proposed architecture surpasses existing MoEs by adaptively assigning the parameter budget to experts while maintaining the same total parameter size and number of experts. |