no code implementations • 1 May 2024 • Zhili Liu, Yunhao Gou, Kai Chen, Lanqing Hong, Jiahui Gao, Fei Mi, Yu Zhang, Zhenguo Li, Xin Jiang, Qun Liu, James T. Kwok
As the capabilities of large language models (LLMs) have expanded dramatically, aligning these models with human values presents a significant challenge, posing potential risks during deployment.
no code implementations • 14 Mar 2024 • Yunhao Gou, Kai Chen, Zhili Liu, Lanqing Hong, Hang Xu, Zhenguo Li, Dit-yan Yeung, James T. Kwok, Yu Zhang
Multimodal large language models (MLLMs) have shown impressive reasoning abilities, which, however, are also more vulnerable to jailbreak attacks than their LLM predecessors.
no code implementations • 19 Dec 2023 • Yunhao Gou, Zhili Liu, Kai Chen, Lanqing Hong, Hang Xu, Aoxue Li, Dit-yan Yeung, James T. Kwok, Yu Zhang
Instruction tuning of Large Vision-language Models (LVLMs) has revolutionized the development of versatile models with zero-shot generalization across a wide range of downstream vision-language tasks.
no code implementations • CVPR 2023 • Yunhao Gou, Tom Ko, Hansi Yang, James Kwok, Yu Zhang, Mingxuan Wang
(2) Under-utilization of the unmasked tokens: CMLM primarily focuses on the masked token but it cannot simultaneously leverage other tokens to learn vision-language associations.
1 code implementation • 2 Mar 2022 • Kai Yi, Xiaoqian Shen, Yunhao Gou, Mohamed Elhoseiny
The main question we address in this paper is how to scale up visual recognition of unseen classes, also known as zero-shot learning, to tens of thousands of categories as in the ImageNet-21K benchmark.
no code implementations • 14 Oct 2021 • Ziyang Wang, Yunhao Gou, Jingjing Li, Yu Zhang, Yang Yang
Zero-shot learning (ZSL) aims to recognize unseen classes based on the knowledge of seen classes.