2 papers
cs.RO2026
Learning to Act While Waiting: RL Finetuning of Generalist Robot Policies Under Inference Latency
Brian Zhu, Momen Khalil, E Harrison +17
While reinforcement learning (RL) allows generalist robot policies to continually improve during deployment, the large model size of modern generalist policies, such as VLAs, poses…
cs.RO2026
On the Efficiency of LoRA Fine-Tuning for Vision-Language-Action Models in Industrial Robotic Manipulation
Finn Ferchau, Daniel Pommer, Cristian Axenie
Deploying billion-parameter Vision-Language-Action (VLA) models on industrial hardware requires fine-tuning to bridge the embodiment gap. Full Fine-Tuning (FFT) provides maximal pl…