5 papers
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…
Galaxea Open-World Dataset and G0 Dual-System VLA Model
Tao Jiang, Tianyuan Yuan, Yicheng Liu +7
We present Galaxea Open-World Dataset, a large-scale, diverse collection of robot behaviors recorded in authentic human living and working environments. All demonstrations are gath…
Conditioning Matters: Training Diffusion Policies is Faster Than You Think
Zibin Dong, Yicheng Liu, Yinchuan Li +2
Diffusion policies have emerged as a mainstream paradigm for building vision-language-action (VLA) models. Although they demonstrate strong robot control capabilities, their traini…
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…