VLA-Pro: Cross-Task Procedural Memory Transfer for Vision-Language-Action Models
VLA-Pro proposes a system that stores task-specific procedural memories as LoRA adapters during training and transfers them during testing to improve cross-task generalization in Vision-Language-Action models. It enhances model performance by dynamically retrieving and fusing relevant past manipulation experiences when tackling new, unseen tasks, leading to significant success rate improvements on robotic manipulation benchmarks.