6 citations · 6 across the 7 of their papers we have counts for
3 papers · 1 filter
TEMPO: Semantic-Action Decoupled RL Post-Training for Vision-Language-Action Models
Ziheng Liu, Quantao Yang
Vision-language-action (VLA) models are commonly adapted to downstream manipulation tasks via supervised fine-tuning (SFT) or online reinforcement learning (RL) post-training. SFT…
FUS3DMaps: Scalable and Accurate Open-Vocabulary Semantic Mapping by 3D Fusion of Voxel- and Instance-Level Layers
Timon Homberger, Finn Lukas Busch, Jesús Gerardo Ortega Peimbert +2
Open-vocabulary semantic mapping enables robots to spatially ground previously unseen concepts without requiring predefined class sets. Current training-free methods commonly rely…
Learning to Localize Reference Trajectories in Image-Space for Visual Navigation
Finn Lukas Busch, Matti Vahs, Quantao Yang +4
We present LoTIS, a model for visual navigation that provides robot-agnostic image-space guidance by localizing a reference RGB trajectory in the robot's current view, without requ…