1 code implementation • 6 May 2024 • Shuhao Mei, Yuxi Zhou, Jiahao Xu, Yuxuan Wan, Shan Cao, Qinghao Zhao, Shijia Geng, Junqing Xie, Shenda Hong
However, these methods fail to early predict an individual's probability of COPD in the future based on subtle features in the spirogram.
1 code implementation • 27 Mar 2024 • Yuxuan Wan, Kaichen Zhou, jinhong Chen, Hao Dong
To support research in this area, we present the LEGO Error Correction Assembly Dataset (LEGO-ECA), comprising manual images for assembly steps and instances of assembly failures.
no code implementations • 25 Mar 2024 • Yunlong Tang, Yuxuan Wan, Lei Qi, Xin Geng
The Style Generation module refreshes all styles at every training epoch, while the Style Removal module eliminates variations in the encoder's output features caused by input styles.
no code implementations • 1 Jan 2024 • Wenxuan Wang, Haonan Bai, Jen-tse Huang, Yuxuan Wan, Youliang Yuan, Haoyi Qiu, Nanyun Peng, Michael R. Lyu
BiasPainter uses a diverse range of seed images of individuals and prompts the image generation models to edit these images using gender, race, and age-neutral queries.
no code implementations • 1 Jan 2024 • Yuxuan Wan, Wenxuan Wang, Yiliu Yang, Youliang Yuan, Jen-tse Huang, Pinjia He, Wenxiang Jiao, Michael R. Lyu
In addition, the test cases of LogicAsker can be further used to design demonstration examples for in-context learning, which effectively improves the logical reasoning ability of LLMs, e. g., 10\% for GPT-4.
1 code implementation • 21 May 2023 • Yuxuan Wan, Wenxuan Wang, Pinjia He, Jiazhen Gu, Haonan Bai, Michael Lyu
Particularly, it is hard to generate inputs that can comprehensively trigger potential bias due to the lack of data containing both social groups as well as biased properties.
no code implementations • 15 Mar 2023 • Haoran Wu, Wenxuan Wang, Yuxuan Wan, Wenxiang Jiao, Michael Lyu
ChatGPT is a cutting-edge artificial intelligence language model developed by OpenAI, which has attracted a lot of attention due to its surprisingly strong ability in answering follow-up questions.
1 code implementation • 18 Oct 2022 • Jie Ren, Han Xu, Yuxuan Wan, Xingjun Ma, Lichao Sun, Jiliang Tang
The unlearnable strategies have been introduced to prevent third parties from training on the data without permission.
no code implementations • 18 Oct 2022 • Han Xu, Xiaorui Liu, Yuxuan Wan, Jiliang Tang
We demonstrate that the fairly trained classifiers can be greatly vulnerable to such poisoning attacks, with much worse accuracy & fairness trade-off, even when we apply some of the most effective defenses (originally proposed to defend traditional classification tasks).
no code implementations • 17 Oct 2022 • Han Xu, Pengfei He, Jie Ren, Yuxuan Wan, Zitao Liu, Hui Liu, Jiliang Tang
To tackle this problem, we propose Probabilistic Categorical Adversarial Attack (PCAA), which transfers the discrete optimization problem to a continuous problem that can be solved efficiently by Projected Gradient Descent.
no code implementations • 1 Jun 2022 • Yuxuan Wan, Han Xu, Xiaorui Liu, Jie Ren, Wenqi Fan, Jiliang Tang
However, federated learning is still under the risk of privacy leakage because of the existence of attackers who deliberately conduct gradient leakage attacks to reconstruct the client data.