10 papers
Can Vision-Language Models Stay Helpful When Facing Implicit Risks? Intent-Privilege OPSD for Efficient Safety-Helpfulness Alignment
Haotian Deng, Wenbin Xing, Gang Xu +5
Vision-Language Models (VLMs) remain vulnerable to cross-modal implicit risks: visual and textual inputs that appear benign in isolation can jointly elicit unsafe responses. Existi…
ORACLE: Anticipating Scams from Partial Trajectories in Streaming App Usage
Wenbo Gao, Songbai Tan, Zhongan Wang +6
Smartphone scams are increasingly prevalent and typically manifest as multi-stage, cross-application processes with gradually emerging intent. Effective intervention thus requires…
RS-WorldModel: a Unified Model for Remote Sensing Understanding and Future Sense Forecasting
Linrui Xu, Zhongan Wang, Fei Shen +4
Remote sensing world models aim to both explain observed changes and forecast plausible futures, two tasks that share spatiotemporal priors. Existing methods, however, typically ad…
Risk Awareness Injection: Calibrating Vision-Language Models for Safety without Compromising Utility
Mengxuan Wang, Yuxin Chen, Gang Xu +3
Vision language models (VLMs) extend the reasoning capabilities of large language models (LLMs) to cross-modal settings, yet remain highly vulnerable to multimodal jailbreak attack…
Yo'City: Personalized and Boundless 3D Realistic City Scene Generation via Self-Critic Expansion
Keyang Lu, Sifan Zhou, Hongbin Xu +6
Realistic 3D city generation is fundamental to a wide range of applications, including virtual reality and digital twins. However, most existing methods rely on training a single d…
StyleTailor: Towards Personalized Fashion Styling via Hierarchical Negative Feedback
Hongbo Ma, Fei Shen, Hongbin Xu +5
The advancement of intelligent agents has revolutionized problem-solving across diverse domains, yet solutions for personalized fashion styling remain underexplored, which holds im…
TextSplat: Text-Guided Semantic Fusion for Generalizable Gaussian Splatting
Zhicong Wu, Hongbin Xu, Gang Xu +6
Recent advancements in Generalizable Gaussian Splatting have enabled robust 3D reconstruction from sparse input views by utilizing feed-forward Gaussian Splatting models, achieving…
Safe-VAR: Safe Visual Autoregressive Model for Text-to-Image Generative Watermarking
Ziyi Wang, Songbai Tan, Gang Xu +5
With the success of autoregressive learning in large language models, it has become a dominant approach for text-to-image generation, offering high efficiency and visual quality. H…
PVChat: Personalized Video Chat with One-Shot Learning
Yufei Shi, Weilong Yan, Gang Xu +6
Video large language models (ViLLMs) excel in general video understanding, e.g., recognizing activities like talking and eating, but struggle with identity-aware comprehension, suc…
Inter3D: A Benchmark and Strong Baseline for Human-Interactive 3D Object Reconstruction
Gan Chen, Ying He, Mulin Yu +5
Recent advancements in implicit 3D reconstruction methods, e.g., neural rendering fields and Gaussian splatting, have primarily focused on novel view synthesis of static or dynamic…