Papers by Shanghua Gao
MoExtend: Tuning New Experts for Modality and Task Extension (2024.acl-srw)
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| Challenge: | Existing instruction tuning methods for large language models (LLMs) are costly and difficult to implement. |
| Approach: | They propose a framework to streamline the modality adaptation and extension of Mixture-of-Experts (MoE) models. |
| Outcome: | The proposed framework enables rapid adaptation and extension to new modal data or tasks without tuning pretrained models. |