VLAQuantBench: Closed-Loop Evaluation of Post-Training Quantization for Vision-Language-Action Models.

arXiv:2609.25376v1 Announce Type: cross Abstract: Post-training quantization reduces the memory requirements of vision-language-action (VLA) models, but precision selection must account for the interaction between layer scope, numerical format, and calibration