4 papers
FlowPRO: Reward-Free Reinforced Fine-Tuning of Flow-Matching VLAs via Proximalized Preference Optimization
Yihao Wu, He Zhang, Junbo Tan +2
Post-training Vision-Language-Action (VLA) models into policies that can be reliably deployed on real robots remains a major bottleneck. SFT and DAgger exploit failure signals only…
PHASER: Phase-Aware and Semantic Experience Replay for Vision-Language-Action Models
Ziyang Chen, Shaoguang Wang, Weiyu Guo +5
Vision-Language-Action (VLA) models have achieved remarkable success in language-conditioned robotic manipulation. However, deploying these models in open-ended environments requir…
Lifelike Agility and Play in Quadrupedal Robots using Reinforcement Learning and Generative Pre-trained Models
Lei Han, Qingxu Zhu, Jiapeng Sheng +16
Knowledge from animals and humans inspires robotic innovations. Numerous efforts have been made to achieve agile locomotion in quadrupedal robots through classical controllers or r…
Neural Categorical Priors for Physics-Based Character Control
Qingxu Zhu, He Zhang, Mengting Lan +1
Recent advances in learning reusable motion priors have demonstrated their effectiveness in generating naturalistic behaviors. In this paper, we propose a new learning framework in…