1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CV2025
AegisRF: Adversarial Perturbations Guided with Sensitivity for Protecting Intellectual Property of Neural Radiance Fields
Woo Jae Kim, Kyu Beom Han, Yoonki Cho +4
As Neural Radiance Fields (NeRFs) have emerged as a powerful tool for 3D scene representation and novel view synthesis, protecting their intellectual property (IP) from unauthorize…
cs.CR2025★ 1 cited
Defending MoE LLMs against Harmful Fine-Tuning via Safety Routing Alignment
Jaehan Kim, Minkyoo Song, Seungwon Shin +1
Recent large language models (LLMs) have increasingly adopted the Mixture-of-Experts (MoE) architecture for efficiency. MoE-based LLMs heavily depend on a superficial safety mechan…
cs.CV2025
AdvPaint: Protecting Images from Inpainting Manipulation via Adversarial Attention Disruption
Joonsung Jeon, Woo Jae Kim, Suhyeon Ha +2
The outstanding capability of diffusion models in generating high-quality images poses significant threats when misused by adversaries. In particular, we assume malicious adversari…