2 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
A Dataset and Benchmark for Copyright Infringement Unlearning from Text-to-Image Diffusion Models
Rui Ma, Qiang Zhou, Yizhu Jin +11
Copyright law confers upon creators the exclusive rights to reproduce, distribute, and monetize their creative works. However, recent progress in text-to-image generation has intro…