DySL-VLA: Efficient Vision-Language-Action Model Inference via Dynamic-Static Layer-Skipping for Robot Manipulation
Published in DAC 2026, 2026
Dynamic-static layer-skipping for vision-language-action models: adaptive layer bypass based on task requirements and motion significance, with 85.7× fewer trainable parameters than full fine-tuning.
Recommended citation: Z. Yang, Y. Qi, T. Xie, B. Yu, S. Liu, and M. Li. "DySL-VLA: Efficient Vision-Language-Action Model Inference via Dynamic-Static Layer-Skipping for Robot Manipulation." Design Automation Conference (DAC), 2026.
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