1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2026
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…
cs.CV2024
SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models
Zilan Wang, Junfeng Guo, Jiacheng Zhu +4
Recent advances in large-scale text-to-image (T2I) diffusion models have enabled a variety of downstream applications, including style customization, subject-driven personalization…
cs.CV2024★ 1 cited
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…