2 citations · 3 across the 5 of their papers we have counts for
5 papers
Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks
Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu +1
With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or unsafe cross-modal associatio…
Exploiting the Final Component of Generator Architectures for AI-Generated Image Detection
Yanzhu Liu, Xiao Liu, Yuexuan Wang +1
With the rapid proliferation of powerful image generators, accurate detection of AI-generated images has become essential for maintaining a trustworthy online environment. However,…
Variance-Reduction Guidance: Sampling Trajectory Optimization for Diffusion Models
Shifeng Xu, Yanzhu Liu, Adams Wai-Kin Kong
Diffusion models have become emerging generative models. Their sampling process involves multiple steps, and in each step the models predict the noise from a noisy sample. When the…
MACE: Mass Concept Erasure in Diffusion Models
Shilin Lu, Zilan Wang, Leyang Li +2
The rapid expansion of large-scale text-to-image diffusion models has raised growing concerns regarding their potential misuse in creating harmful or misleading content. In this pa…
TF-ICON: Diffusion-Based Training-Free Cross-Domain Image Composition
Shilin Lu, Yanzhu Liu, Adams Wai-Kin Kong
Text-driven diffusion models have exhibited impressive generative capabilities, enabling various image editing tasks. In this paper, we propose TF-ICON, a novel Training-Free Image…