ACM: Digital Library: Communications of the ACM ACM Digital Library Communications of the
ACM Volume 67, Number 4 (2024), Pages 50-59 The Science of Detecting LLM-Generated Text …

Federated learning (FL) has attracted growing attentions via data-private collaborative
training on decentralized clients. However, most existing methods unrealistically assume …

The prosperity of deep neural networks (DNNs) is largely benefited from open-source
datasets, based on which users can evaluate and improve their methods. In this paper, we …

Federated learning-based semantic segmentation (FSS) has drawn widespread attention
via decentralized training on local clients. However, most FSS models assume categories …

Deep neural networks (DNNs) are vulnerable to backdoor attacks, where adversaries
embed a hidden backdoor trigger during the training process for malicious prediction …

While real-world applications of reinforcement learning (RL) are becoming popular, the
security and robustness of RL systems are worthy of more attention and exploration. In …

Self-supervised models are increasingly prevalent in machine learning (ML) since they
reduce the need for expensively labeled data. Because of their versatility in downstream …

Deep Neural Networks (DNNs), from AlexNet to ResNet to ChatGPT, have made
revolutionary progress in recent years, and are widely used in various fields. The high …

As the scientific and technological achievements produced by human intellectual labor and
computation cost, model intellectual property (IP) protection, which refers to preventing the …

Non-transferable learning (NTL) aims to restrict the generalization of models toward the
target domain (s). To this end, existing works learn non-transferable representations by …