1 code implementation • 24 Jan 2025 • Zhong Li, Yuhang Wang, Matthijs van Leeuwen
Self-supervised learning (SSL) is an emerging paradigm that exploits supervisory signals generated from the data itself, and many recent studies have leveraged SSL to conduct graph anomaly detection.
no code implementations • 15 Jan 2025 • Zhenxing Niu, Haoxuan Ji, Yuyao Sun, Zheng Lin, Fei Gao, Yuhang Wang, Haichao Gao
To achieve aligned data forgetting, we propose a Twin Machine Unlearning (TMU) approach, where a twin unlearning problem is defined corresponding to the original unlearning problem.
no code implementations • 6 Jan 2025 • Yuhang Wang, Abdulaziz Alhuraish, Shengming Yuan, Shuyi Wang, Hao Zhou
The Lane Keeping Assist (LKA) system has become a standard feature in recent car models.
1 code implementation • 22 Dec 2024 • Yuxiang Zhang, YuQi Yang, Jiangming Shu, Yuhang Wang, Jinlin Xiao, Jitao Sang
OpenAI's recent introduction of Reinforcement Fine-Tuning (RFT) showcases the potential of reasoning foundation model and offers a new paradigm for fine-tuning beyond simple pattern imitation.
1 code implementation • 26 Nov 2024 • Yuhang Wang, Yuxiang Zhang, Yanxu Zhu, Xinyan Wen, Jitao Sang
In our preliminary research, we conducted safety evaluations of the o1 model, including complex jailbreak attack scenarios using adversarial natural language prompts and mathematical encoding prompts.
no code implementations • 8 Nov 2024 • Honghao Shi, Longkai Cheng, Wenli Wu, Yuhang Wang, Xuan Liu, Shaokai Nie, Weixv Wang, Xuebin Min, Chunlei Men, Yonghua Lin
Recent advancements in Large Language Models (LLMs) and related technologies such as Retrieval-Augmented Generation (RAG) and Diagram of Thought (DoT) have enabled the creation of autonomous intelligent systems capable of performing cluster diagnostics and troubleshooting.
1 code implementation • 8 Jul 2024 • Yanxu Zhu, Jinlin Xiao, Yuhang Wang, Jitao Sang
Recent studies have demonstrated that large language models (LLMs) are susceptible to being misled by false premise questions (FPQs), leading to errors in factual knowledge, know as factuality hallucination.
1 code implementation • 10 Jun 2024 • Zhong Li, Simon Geisler, Yuhang Wang, Stephan Günnemann, Matthijs van Leeuwen
In this paper we demonstrate that these explanations can unfortunately not be trusted, as common GNN explanation methods turn out to be highly susceptible to adversarial perturbations.
no code implementations • 28 Mar 2024 • Muzi Chen, Yuhang Wang, Boyao Wu, Difang Huang
The interactive effect is significant in the Chinese stock market, exacerbating the abnormal market volatilities and risk contagion.
1 code implementation • 1 Feb 2024 • Jitao Sang, Yuhang Wang, Jing Zhang, Yanxu Zhu, Chao Kong, Junhong Ye, Shuyu Wei, Jinlin Xiao
In the first phase, based on human supervision, the quality of weak supervision is enhanced through a combination of scalable oversight and ensemble learning, reducing the capability gap between weak teachers and strong students.
1 code implementation • 28 Nov 2023 • Yuhang Wang, Yanxu Zhu, Chao Kong, Shuyu Wei, Xiaoyuan Yi, Xing Xie, Jitao Sang
This benchmark serves as a valuable resource for cultural studies in LLMs, paving the way for more culturally aware and sensitive models.
1 code implementation • 13 Nov 2023 • Junyang Wang, Yuhang Wang, Guohai Xu, Jing Zhang, Yukai Gu, Haitao Jia, Jiaqi Wang, Haiyang Xu, Ming Yan, Ji Zhang, Jitao Sang
Despite making significant progress in multi-modal tasks, current Multi-modal Large Language Models (MLLMs) encounter the significant challenge of hallucinations, which may lead to harmful consequences.
no code implementations • 11 Oct 2023 • Zhongji Zhang, Yuhang Wang, Yinghao Zhu, Xinyu Ma, Tianlong Wang, Chaohe Zhang, Yasha Wang, Liantao Ma
Due to the limited information about emerging diseases, symptoms are hard to be noticed and recognized, so that the window for clinical intervention could be ignored.
no code implementations • ICCV 2023 • Enze Ye, Yuhang Wang, Hong Zhang, Yiqin Gao, Huan Wang, He Sun
To our knowledge, our work is the first attempt to directly recover 3D structures of a temporally-varying particle from liquid-phase EM movies.
Cryogenic Electron Microscopy (cryo-EM)
Object Reconstruction
+1
no code implementations • 9 Aug 2023 • WeiJie Chen, Yuhang Wang, Lin Yao
In these methods, only a subset of the input dataset is needed to train neural networks for the estimation of poses and conformations.
no code implementations • 7 Aug 2023 • WeiJie Chen, Xinyan Wang, Yuhang Wang
This has inspired us to combine fragment recognition and structure prediction methods to build a complete structure.
no code implementations • 4 Aug 2023 • Yuhang Wang, Yuxiang Zhang, Dongyuan Lu, Jitao Sang
Many news comment mining studies are based on the assumption that comment is explicitly linked to the corresponding news.
1 code implementation • 6 Jun 2023 • Yuhang Wang, Dongyuan Lu, Chao Kong, Jitao Sang
Many works employed prompt tuning methods to automatically optimize prompt queries and extract the factual knowledge stored in Pretrained Language Models.
no code implementations • 6 May 2023 • Ruijia Wu, Yuhang Wang, Huafeng Shi, Zhipeng Yu, Yichao Wu, Ding Liang
In this paper, we propose the Adversarial Decoupling Augmentation Framework (ADAF), addressing these issues by targeting the image-text fusion module to enhance the defensive performance of facial privacy protection algorithms.
no code implementations • 13 Feb 2023 • Lin Yao, Ruihan Xu, Zhifeng Gao, Guolin Ke, Yuhang Wang
The central problem in cryo-electron microscopy (cryo-EM) is to recover the 3D structure from noisy 2D projection images which requires estimating the missing projection angles (poses).
no code implementations • 2 Feb 2023 • Lingli He, Jiahui Sun, Yiwei Gao, Bin Li, Yuhang Wang, Yanli Dong, Weidong An, Hang Li, Bei Yang, Yuhan Ge, Xuejun Cai Zhang, Yun Stone Shi, Yan Zhao
Glutamate-gated kainate receptors (KARs) are ubiquitous in the central nervous system of vertebrates, mediate synaptic transmission on post-synapse, and modulate transmitter release on pre-synapse.
no code implementations • CVPR 2023 • WeiJie Chen, Xinyan Wang, Yuhang Wang
This has inspired us to combine fragment recognition and structure prediction methods to build a complete structure.
no code implementations • 12 Sep 2022 • Yuhang Wang, Huafeng Shi, Rui Min, Ruijia Wu, Siyuan Liang, Yichao Wu, Ding Liang, Aishan Liu
Most detection methods are designed to verify whether a model is infected with presumed types of backdoor attacks, yet the adversary is likely to generate diverse backdoor attacks in practice that are unforeseen to defenders, which challenge current detection strategies.
no code implementations • 30 May 2022 • Yuhang Wang, Li Wang, Yanjie Yang, Yilin Zhang
Finally, the two EDU representations are incorporated as the enhanced text representation for fake news detection, using a gated recursive unit combined with a global attention mechanism.
no code implementations • 27 Sep 2021 • Xuyan Tan, Yuhang Wang, Bowen Du, Junchen Ye, Weizhong Chen, Leilei Sun, Liping Li
Mechanical analysis for the full face of tunnel structure is crucial to maintain stability, which is a challenge in classical analytical solutions and data analysis.
no code implementations • 1 Mar 2021 • Xiuqing Li, Wei Li, Xinlin Yi, Qihang Huang, Yuhang Wang, Chenzhe Ye
With the path-specific parameters obtained by the proposed channel tracking, the proposed PTRM can not only match the time dispersion as conventional PTRM, but also the doubly-spread channel, since the path-specific delay and Doppler scaler factor can help to match the channel in both time and frequency domain.
no code implementations • 1 Mar 2021 • Qihang Huang, Wei Li, Weicheng Zhan, Yuhang Wang, Rongrong Guo
A model based on the underwater acoustic channel's correlation can be used as the state-space model in the Kalman filter to improve the underwater acoustic channel tracking compared that without a model.
1 code implementation • Expert Systems with Applications 2020 • Yuhang Wang, Li Wang, Yanjie Yang, Tao Lian
In this paper, we propose a novel graph-based neural network model named SemSeq4FD for early fake news detection based on enhanced text representations.
no code implementations • ICCV 2019 • Jun Fu, Jing Liu, Yuhang Wang, Yong Li, Yongjun Bao, Jinhui Tang, Hanqing Lu
Recent works attempt to improve scene parsing performance by exploring different levels of contexts, and typically train a well-designed convolutional network to exploit useful contexts across all pixels equally.
Ranked #76 on
Semantic Segmentation
on ADE20K val
no code implementations • 16 Aug 2017 • Jun Fu, Jing Liu, Yuhang Wang, Hanqing Lu
In SDN, multiple shallow deconvolutional networks, which are called as SDN units, are stacked one by one to integrate contextual information and guarantee the fine recovery of localization information.
Ranked #4 on
Semantic Segmentation
on PASCAL VOC 2012 test
1 code implementation • CVPR 2016 • Jiaxiang Wu, Cong Leng, Yuhang Wang, Qinghao Hu, Jian Cheng
Recently, convolutional neural networks (CNN) have demonstrated impressive performance in various computer vision tasks.