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cs.LG2026
Mitigating Semantic Collapse in Generative Personalization with Test-Time Embedding Adjustment
Anh Bui, Trang Vu, Trung Le +5
In this paper, we investigate the semantic collapsing problem in generative personalization, an under-explored topic where the learned visual concept () gradually shifts from it…
cs.LG2025
Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them
Anh Bui, Trang Vu, Long Vuong +5
Concept erasure has emerged as a promising technique for mitigating the risk of harmful content generation in diffusion models by selectively unlearning undesirable concepts. The c…
cs.LG2024
A Survey on Adversarial Robustness of LiDAR-based Machine Learning Perception in Autonomous Vehicles
Junae Kim, Amardeep Kaur
In autonomous driving, the combination of AI and vehicular technology offers great potential. However, this amalgamation comes with vulnerabilities to adversarial attacks. This sur…