Summary of Steerdiff: Steering Towards Safe Text-to-image Diffusion Models, by Hongxiang Zhang et al.
SteerDiff: Steering towards Safe Text-to-Image Diffusion Modelsby Hongxiang Zhang, Yifeng He, Hao ChenFirst submitted to…
SteerDiff: Steering towards Safe Text-to-Image Diffusion Modelsby Hongxiang Zhang, Yifeng He, Hao ChenFirst submitted to…
Mitigating Semantic Leakage in Cross-lingual Embeddings via Orthogonality Constraintby Dayeon Ki, Cheonbok Park, Hyunjoong KimFirst…
Context-Aware Temporal Embedding of Objects in Video Databy Ahnaf Farhan, M. Shahriar HossainFirst submitted to…
Contrasting Deepfakes Diffusion via Contrastive Learning and Global-Local Similaritiesby Lorenzo Baraldi, Federico Cocchi, Marcella Cornia,…
Addressing Imbalance for Class Incremental Learning in Medical Image Classificationby Xuze Hao, Wenqian Ni, Xuhao…
Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasksby Antoni Kowalczuk, Jan Dubiński, Atiyeh Ashari Ghomi,…
Contrastive Learning of Preferences with a Contextual InfoNCE Lossby Timo Bertram, Johannes Fürnkranz, Martin MüllerFirst…
Rethinking and Defending Protective Perturbation in Personalized Diffusion Modelsby Yixin Liu, Ruoxi Chen, Xun Chen,…
Negative Prototypes Guided Contrastive Learning for WSODby Yu Zhang, Chuang Zhu, Guoqing Yang, Siqi ChenFirst…
Aligning Diffusion Models with Noise-Conditioned Perceptionby Alexander Gambashidze, Anton Kulikov, Yuriy Sosnin, Ilya MakarovFirst submitted…