3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.AI2024
Defending Large Language Models Against Jailbreak Attacks via Layer-specific Editing
Wei Zhao, Zhe Li, Yige Li +2
Large language models (LLMs) are increasingly being adopted in a wide range of real-world applications. Despite their impressive performance, recent studies have shown that LLMs ar…
cs.LG2024
Widely Linear Matched Filter: A Lynchpin towards the Interpretability of Complex-valued CNNs
Qingchen Wang, Zhe Li, Zdenka Babic +3
A recent study on the interpretability of real-valued convolutional neural networks (CNNs) {Stankovic_Mandic_2023CNN} has revealed a direct and physically meaningful link with the…
cs.LG2023★ 3 cited
Balancing Privacy Protection and Interpretability in Federated Learning
Zhe Li, Honglong Chen, Zhichen Ni +1
Federated learning (FL) aims to collaboratively train the global model in a distributed manner by sharing the model parameters from local clients to a central server, thereby poten…