3 papers
cs.RO2026
Latent Policy Steering through One-Step Flow Policies
Hokyun Im, Andrey Kolobov, Jianlong Fu +1
Offline reinforcement learning (RL) allows robots to learn from offline datasets without risky exploration. Yet, offline RL's performance often hinges on a brittle trade-off betwee…
cs.CV2026
ComPose: When to Trust Hands for Object Pose Tracking
Jisu Shin, Junoh Lee, JunGyu Lee +5
Reconstructing the motion of objects from videos is a key component for embodied AI and robot manipulation. While diverse approaches to object pose tracking have been studied, they…
cs.RO2026
TwinVLA: Data-Efficient Bimanual Manipulation with Twin Single-Arm Vision-Language-Action Models
Hokyun Im, Euijin Jeong, Andrey Kolobov +2
Vision-language-action models (VLAs) trained on large-scale robotic datasets have demonstrated strong performance on manipulation tasks, including bimanual tasks. However, because…