7 accepted papers
Latent Diffusion Models have become a powerful tool for generating high-fidelity unrestricted adversarial examples. However, the existing methods typically perturb only the initial latent or rely on prompt engineering, which is ill-suited to the iterative nature of the diffusion process, plus optimi
Mixture-of-Experts (MoE) is a sparse neural architecture that significantly increases model capacity while maintaining low computational complexity. However, deploying MoE-based large language models (LLMs) on memory-constrained edge devices remains challenging due to their substantial memory requir
In recent years, RF fingerprinting (RFF) has emerged as a promising technology for wireless device authentication. However, temporal variations in device load and temperature, along with channel effects, lead to inconsistencies in RFF distributions between training and testing phases. As a result,
Deep learning models are well known to be susceptible to backdoor attacks, and text-to-image generation models are no exception. When a specific trigger is embedded in the input, a backdoored model can be manipulated to perform attacker-defined malicious behaviors, such as generating harmful or inap
The recent flourish of deep learning on various tasks is largely accredited to the rich and high-quality labeled data. Nonetheless, collecting sufficient labeled samples is not very practical for many real applications. Few-shot Learning (FSL) provides a promising solution that allows a model to lea…
Mode decomposition methods are the current workhorse for the analysis of non-stationary signals. However, current attempts at these methods mainly focus on improving accuracy, leaving computational efficiency untouched. To this end, we leverage the neural mode decomposition technique and propose an…
We study the problem of object reconstruction in a multi-agent collaboration scenario. Specifically, we focus on the reconstruction of specific goals through several cooperative agents equipped with vision sensors to achieve higher efficiency than single agents. Our main insight is that a complete 3…