Deep Learning
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions
AI safety has long been an important issue in the deep learning community.
Advancing Model Pruning via Bi-level Optimization
As illustrated by the Lottery Ticket Hypothesis (L TH), pruning also has the potential of improving their generalization ability. At the core of L TH, iterative magnitude pruning (IMP) is the predominant pruning method to successfully find'winning tickets'. Y et, the computation cost of IMP grows prohibitively as the targeted pruning ratio increases. To reduce the computation overhead, various efficient'one-shot' pruning methods have been developed but these schemes are usually
Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation Appendix
The summary of the datasets are listed in Table 1.
Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation Ying Sun
While it is expected to understand their intrinsic decision-making processes, these deep neural networks often work in a black-box way.
Watermarking Makes Language Models Radioactive Tom Sander
Current methods like membership inference or active IP protection either work only in settings where the suspected text is known or do not provide reliable statistical guarantees. We discover that, on the contrary, it is possible to reliably determine if a language model was trained on synthetic data if that data is output by a watermarked LLM.