1 citations · 1 across the 4 of their papers we have counts for
4 papers
Robust Bimanual Vision-Language-Action Models via Embarrassingly Simple Modality Masking
Dongzhou Cheng, Ziang Li, Yixiao Zhou +6
Query-based Vision-Language-Action (VLA) models offer low-latency inference that is attractive for bimanual robotic manipulation, but we observe that they can still exhibit discont…
Light-WAM: Efficient World Action Models with State-Fusion Action Decoding
Ziang Li, Dongzhou Cheng, Yibin Wang +5
World Action Models (WAMs) extend robot policy learning by incorporating future prediction as an additional training objective, encouraging the policy to encode task-relevant tempo…
From Head to Tail: Efficient Black-box Model Inversion Attack via Long-tailed Learning
Ziang Li, Hongguang Zhang, Juan Wang +6
Model Inversion Attacks (MIAs) aim to reconstruct private training data from models, leading to privacy leakage, particularly in facial recognition systems. Although many studies h…
A Stealthy Wrongdoer: Feature-Oriented Reconstruction Attack against Split Learning
Xiaoyang Xu, Mengda Yang, Wenzhe Yi +5
Split Learning (SL) is a distributed learning framework renowned for its privacy-preserving features and minimal computational requirements. Previous research consistently highligh…