12 citations · 33 across the 5 of their papers we have counts for
6 papers
LRR-Bench: Left, Right or Rotate? Vision-Language models Still Struggle With Spatial Understanding Tasks
Fei Kong, Jinhao Duan, Kaidi Xu +3
Real-world applications, such as autonomous driving and humanoid robot manipulation, require precise spatial perception. However, it remains underexplored how Vision-Language Model…
TruthPrInt: Mitigating Large Vision-Language Models Object Hallucination Via Latent Truthful-Guided Pre-Intervention
Jinhao Duan, Fei Kong, Hao Cheng +6
Object Hallucination (OH) has been acknowledged as one of the major trustworthy challenges in Large Vision-Language Models (LVLMs). Recent advancements in Large Language Models (LL…
ACT-Diffusion: Efficient Adversarial Consistency Training for One-step Diffusion Models
Fei Kong, Jinhao Duan, Lichao Sun +6
Though diffusion models excel in image generation, their step-by-step denoising leads to slow generation speeds. Consistency training addresses this issue with single-step sampling…
Exposing the Fake: Effective Diffusion-Generated Images Detection
Ruipeng Ma, Jinhao Duan, Fei Kong +2
Image synthesis has seen significant advancements with the advent of diffusion-based generative models like Denoising Diffusion Probabilistic Models (DDPM) and text-to-image diffus…
An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization
Fei Kong, Jinhao Duan, RuiPeng Ma +4
Recently, diffusion models have achieved remarkable success in generating tasks, including image and audio generation. However, like other generative models, diffusion models are p…
Are Diffusion Models Vulnerable to Membership Inference Attacks?
Jinhao Duan, Fei Kong, Shiqi Wang +2
Diffusion-based generative models have shown great potential for image synthesis, but there is a lack of research on the security and privacy risks they may pose. In this paper, we…