no code implementations • 3 Sep 2024 • Jiangyi Deng, Xinfeng Li, Yanjiao Chen, Yijie Bai, Haiqin Weng, Yan Liu, Tao Wei, Wenyuan Xu
We have created a large-scale dataset for training and conducted extensive experiments to evaluate the capability of Raconteur in shell command explanation.
1 code implementation • 23 Jul 2024 • Rongwu Xu, Yishuo Cai, Zhenhong Zhou, Renjie Gu, Haiqin Weng, Yan Liu, Tianwei Zhang, Wei Xu, Han Qiu
To improve, we propose fine-tuning LLMs with preference learning, emphasizing the preference for timely course-correction.
1 code implementation • 19 Apr 2024 • Jiangyi Deng, Shengyuan Pang, Yanjiao Chen, Liangming Xia, Yijie Bai, Haiqin Weng, Wenyuan Xu
In addition, we carefully design the optimization process to entrap the pre-trained model within a hard-to-escape local optimum regarding restricted domains.
no code implementations • 6 Feb 2024 • Lei Yu, Meng Han, Yiming Li, Changting Lin, Yao Zhang, Mingyang Zhang, Yan Liu, Haiqin Weng, Yuseok Jeon, Ka-Ho Chow, Stacy Patterson
Vertical Federated Learning (VFL) is a federated learning paradigm where multiple participants, who share the same set of samples but hold different features, jointly train machine learning models.
1 code implementation • 11 Nov 2023 • Peiyu Liu, Junming Liu, Lirong Fu, Kangjie Lu, Yifan Xia, Xuhong Zhang, Wenzhi Chen, Haiqin Weng, Shouling Ji, Wenhai Wang
Prior works show that ChatGPT has the capabilities of processing foundational code analysis tasks, such as abstract syntax tree generation, which indicates the potential of using ChatGPT to comprehend code syntax and static behaviors.
no code implementations • 20 Jun 2023 • Hongwei Yao, Zheng Li, Haiqin Weng, Feng Xue, Zhan Qin, Kui Ren
FDINET exhibits the capability to identify colluding adversaries with an accuracy exceeding 91%.
no code implementations • ICCV 2023 • Xue Wang, Zhibo Wang, Haiqin Weng, Hengchang Guo, Zhifei Zhang, Lu Jin, Tao Wei, Kui Ren
Considering the insufficient study on such complex causal questions, we make the first attempt to explain different causal questions by contrastive explanations in a unified framework, ie., Counterfactual Contrastive Explanation (CCE), which visually and intuitively explains the aforementioned questions via a novel positive-negative saliency-based explanation scheme.
no code implementations • 3 Jun 2021 • Ang Li, Qiuhong Ke, Xingjun Ma, Haiqin Weng, Zhiyuan Zong, Feng Xue, Rui Zhang
A promising countermeasure against such forgeries is deep inpainting detection, which aims to locate the inpainted regions in an image.