2 papers
cs.RO2026
ACE-Ego-0: Unifying Egocentric Human and Robotic Data for VLA Pretraining
Hao Li, Ganlong Zhao, Yufei Liu +8
Vision-Language-Action (VLA) models benefit from large-scale and diverse embodied data, yet scaling robot trajectory collection is costly and labor-intensive. Recent advances show…
cs.RO2026
Hierarchical Advantage Weighting for Online RL Fine-Tuning of VLAs from Sparse Episode Outcomes
Tongyan Fang, Siyuan Huang, Naiyu Fang +6
When pretrained VLA policies are fine-tuned through online RL, each rollout episode produces only a single binary outcome (success or failure), yet the actor update requires per-tr…