4 papers · 1 filter
Fast-WAM: Do World Action Models Need Test-time Future Imagination?
Tianyuan Yuan, Zibin Dong, Yicheng Liu +1
World Action Models (WAMs) have emerged as a promising alternative to Vision-Language-Action (VLA) models for embodied control because they explicitly model how visual observations…
FASTer: Toward Efficient Autoregressive Vision Language Action Modeling via Neural Action Tokenization
Yicheng Liu, Shiduo Zhang, Zibin Dong +12
Autoregressive vision-language-action (VLA) models have recently demonstrated strong capabilities in robotic manipulation. However, their core process of action tokenization often…
DepthVLA: Enhancing Vision-Language-Action Models with Depth-Aware Spatial Reasoning
Tianyuan Yuan, Yicheng Liu, Chenhao Lu +3
Vision-Language-Action (VLA) models have recently shown impressive generalization and language-guided manipulation capabilities. However, their performance degrades on tasks requir…
Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving
Yunshen Wang, Yicheng Liu, Tianyuan Yuan +4
Accurately predicting 3D occupancy grids from visual inputs is critical for autonomous driving, but current discriminative methods struggle with noisy data, incomplete observations…