📄 中文摘要
VLA-适配器是一种新兴的模型架构，旨在有效整合视觉、语言和行动三种模态，特别适用于资源受限的环境。该模型通过引入适配器机制，能够在小规模数据集上实现高效的学习和推理。研究表明，VLA-适配器在多个基准任务中表现出色，展示了其在多模态任务中的潜力。该方法不仅提高了模型的灵活性，还降低了训练和推理的计算成本，适合在移动设备和边缘计算场景中应用。未来的研究可以进一步优化该模型，以增强其在更复杂任务中的表现。
VLA-适配器：一种有效的小规模视觉-语言-行动模型范式
📄 English Summary
VLA-Adapter: An Effective Paradigm for Tiny-Scale Vision-Language-Action Model
The VLA-Adapter is an emerging model architecture designed to effectively integrate vision, language, and action modalities, particularly in resource-constrained environments. By introducing an adapter mechanism, the model achieves efficient learning and inference on small-scale datasets. Research demonstrates that the VLA-Adapter excels in various benchmark tasks, showcasing its potential in multimodal applications. This approach not only enhances model flexibility but also reduces computational costs during training and inference, making it suitable for deployment on mobile devices and edge computing scenarios. Future research may focus on further optimizing the model to improve its performance on more complex tasks.