6 citations · 6 across the 8 of their papers we have counts for
8 papers
NavCMPO: Critic-Guided MeanFlow Policy Optimization for Adaptive Navigation
Junjie An, Yi Wu, Xiao Liu +5
End-to-end diffusion-based policies have demonstrated strong performance in mapless visual navigation, but their iterative denoising process introduces substantial inference latenc…
SoftNav: Injecting 3D Scene Tokens into VLMs for Embodied Navigation
Yi Wu, Junjie An, Xiao Liu +6
In goal-directed embodied navigation, where an agent must locate a specified target in an unseen environment, 3D scene understanding and navigation reasoning must work in concert.…
Closed-Loop Bidirectional Prompting for Adversarial Robustness of Vision Language Models
Xiao Liu, Jiaxiang Liu, Boci Peng +6
Vision Language Models adapt well to downstream tasks but are highly vulnerable to adversarial perturbations that disrupt cross-modal semantic alignment. Existing defenses are larg…
Accelerating Rectified Flow Models via Trajectory-Aware Caching
Xiao Liu, Kai Liu, Naiyang Guan +5
Diffusion and rectified flow (RF) models generate high-fidelity images and videos, but their iterative velocity-field evaluations are computationally expensive. Existing caching me…
Self-Calibrated Consistency can Fight Back for Adversarial Robustness in Vision-Language Models
Jiaxiang Liu, Jiawei Du, Xiao Liu +2
Pre-trained vision-language models (VLMs) such as CLIP have demonstrated strong zero-shot capabilities across diverse domains, yet remain highly vulnerable to adversarial perturbat…
Towards Adaptive Meta-Gradient Adversarial Examples for Visual Tracking
Wei-Long Tian, Peng Gao, Xiao Liu +4
In recent years, visual tracking methods based on convolutional neural networks and Transformers have achieved remarkable performance and have been successfully applied in fields s…
Redistribute Ensemble Training for Mitigating Memorization in Diffusion Models
Xiaoliu Guan, Yu Wu, Huayang Huang +3
Diffusion models, known for their tremendous ability to generate high-quality samples, have recently raised concerns due to their data memorization behavior, which poses privacy ri…
Iterative Ensemble Training with Anti-Gradient Control for Mitigating Memorization in Diffusion Models
Xiao Liu, Xiaoliu Guan, Yu Wu +1
Diffusion models, known for their tremendous ability to generate novel and high-quality samples, have recently raised concerns due to their data memorization behavior, which poses…