11 papers
Black-Box Adversarial Patch Attacks on VLAs via Ancestor VLM Exploitation
Xiaoyi Pang, Haoyue Feng, Quanxin Shou +3
Vision-Language-Action models (VLAs) are increasingly deployed in safety-critical physical environments, yet their adversarial robustness remains poorly understood. Existing attack…
World Action Learning via Interaction-Centric Spectral Latent Guidance
Zhiming Liu, Yikun Miao, Ying Chen +7
Learning general-purpose robot policies requires large-scale real-world interaction data, yet collecting robot demonstrations remains expensive and difficult to scale. Egocentric v…
SteerQuant: Steering Quantization Error with Action-Guided Scaling in World-Action Models
Yunhan Wang, Haodong Wang, Zhiming Liu +7
World-action models (WAMs) jointly generate future world states and actions through iterative denoising, using shared weights to process heterogeneous semantic streams of video, pr…
OnlineWM: Causality-Aware Active Online Learning for Effective World Modeling
Yikun Miao, Fangqi Zhu, Quanxin Shou +6
Generative world models aim to predict future states conditioned on actions, where action controllability is fundamental for reliable dynamics modeling. While recent efforts levera…
RedFlow: Redirect Failure into Action-level Corrections for Flow-matching VLA Policy
Zhengyang Yan, Junhao Li, Fangqi Zhu +6
Reinforcement learning (RL) can improve Vision-Language-Action (VLA) policies from deployment experience, but reward- and preference-based RL primarily identifies desirable behavio…
MosaicQuant: Inlier-Outlier Disaggregation for Unified 4-Bit LLM Quantization
Yangjia Hu, Haodong Wang, Zicong Hong +8
4-bit quantization significantly reduces the memory footprint and accelerates the inference of large language models (LLMs). However, its limited bit-width representation struggles…
3D Generation for Embodied AI and Robotic Simulation: A Survey
Tianwei Ye, Yifan Mao, Minwen Liao +6
Embodied AI and robotic systems increasingly depend on scalable, diverse, and physically grounded 3D content for simulation-based training and real-world deployment. While 3D gener…
OpenSearch-VL: An Open Recipe for Frontier Multimodal Search Agents
Shuang Chen, Kaituo Feng, Hangting Chen +7
Deep search has become a crucial capability for frontier multimodal agents, enabling models to solve complex questions through active search, evidence verification, and multi-step…
Unify-Agent: A Unified Multimodal Agent for World-Grounded Image Synthesis
Shuang Chen, Quanxin Shou, Hangting Chen +16
Unified multimodal models provide a natural and promising architecture for understanding diverse and complex real-world knowledge while generating high-quality images. However, the…
HALO: A Unified Vision-Language-Action Model for Embodied Multimodal Chain-of-Thought Reasoning
Quanxin Shou, Fangqi Zhu, Shawn Chen +9
Vision-Language-Action (VLA) models have shown strong performance in robotic manipulation, but often struggle in long-horizon or out-of-distribution scenarios due to the lack of ex…
WMPO: World Model-based Policy Optimization for Vision-Language-Action Models
Fangqi Zhu, Zhengyang Yan, Zicong Hong +3
Vision-Language-Action (VLA) models have shown strong potential for general-purpose robotic manipulation, but their reliance on expert demonstrations limits their ability to learn…