12 papers
Towards the Connection between Activation Sparsity and Flat Minima
Ze Peng, Jian Zhang, Lei Qi +2
The observation that activation sparsity emerges in MLP blocks of standardly trained Transformers offers an opportunity to drastically reduce computation costs without sacrificing…
Architecture-Agnostic Feature Synergy for Universal Defense Against Heterogeneous Generative Threats
Bingxue Zhang, Yang Gao, Feida Zhu +2
Generative AI deployment poses unprecedented challenges to content safety and privacy. However, existing defense mechanisms are often tailored to specific architectures (e.g., Diff…
Leveraging Flatness to Improve Information-Theoretic Generalization Bounds for SGD
Ze Peng, Jian Zhang, Yisen Wang +3
Information-theoretic (IT) generalization bounds have been used to study the generalization of learning algorithms. These bounds are intrinsically data- and algorithm-dependent so…
MAGIC: Achieving Superior Model Merging via Magnitude Calibration
Yayuan Li, Jian Zhang, Jintao Guo +4
The proliferation of pre-trained models has given rise to a wide array of specialised, fine-tuned models. Model merging aims to merge the distinct capabilities of these specialised…
On the Implicit Adversariality of Catastrophic Forgetting in Deep Continual Learning
Ze Peng, Jian Zhang, Jintao Guo +3
Continual learning seeks the human-like ability to accumulate new skills in machine intelligence. Its central challenge is catastrophic forgetting, whose underlying cause has not b…
An Adaptor for Triggering Semi-Supervised Learning to Out-of-Box Serve Deep Image Clustering
Yue Duan, Lei Qi, Yinghuan Shi +1
Recently, some works integrate SSL techniques into deep clustering frameworks to enhance image clustering performance. However, they all need pretraining, clustering learning, or a…