5 papers
MatchingPolicy: Correspondence-Aware Policy Enables Cross-Object In-Context Learning
Qijin She, Hanyang Yu, Zeming Li +1
In-context imitation learning enables few-shot policy generalization but struggles to maintain performance on unseen objects and novel scenarios. To address this, we introduce Matc…
GeniWorld: A Generalizable Interactive World Model for Robotic Manipulation via Visual Actions
Chenghao Gu, Hanyang Yu, Jingbo Zhang +7
Generalist robot policies exhibit strong capabilities, but their robustness in complex and unseen environments remains limited. Scaling robot learning and evaluation in diverse rea…
MaskWAM: Unifying Mask Prompting and Prediction for World-Action Models
Hanyang Yu, Haitao Lin, Jingbo Zhang +4
World Action Models (WAMs) present a promising paradigm for robotic control via video prediction. However, current WAMs suffer from fundamental spatial bottlenecks: standard text i…
Universal Pose Pretraining for Generalizable Vision-Language-Action Policies
Haitao Lin, Hanyang Yu, Jingshun Huang +5
Existing Vision-Language-Action (VLA) models often suffer from feature collapse and low training efficiency because they entangle high-level perception with sparse, embodiment-spec…
LM-Gaussian: Boost Sparse-view 3D Gaussian Splatting with Large Model Priors
Hanyang Yu, Xiaoxiao Long, Ping Tan
We aim to address sparse-view reconstruction of a 3D scene by leveraging priors from large-scale vision models. While recent advancements such as 3D Gaussian Splatting (3DGS) have…