Zobrazeno 1 - 10
of 717
pro vyhledávání: '"CHENG Zhiyuan"'
Autor:
Cheng, Zhiyuan, Wang, Yaojia, Wu, Heng, Ali, Mazhar N., Chan, Julia Y., Bhattacharyya, Semonti
Kagome materials are known to be an ideal platform that hosts a plethora of interesting phases such as topological states, electronic correlation, and magnetism, owing to their unique band structure and geometry. We report magnetotransport measuremen
Externí odkaz:
http://arxiv.org/abs/2410.23872
Autor:
Zhang, Haichuan, Lin, Meiyu, Liu, Zhaoyi, Li, Renyuan, Cheng, Zhiyuan, Yang, Carl, Tang, Mingjie
As generative models achieve great success, tampering and modifying the sensitive image contents (i.e., human faces, artist signatures, commercial logos, etc.) have induced a significant threat with social impact. The backdoor attack is a method that
Externí odkaz:
http://arxiv.org/abs/2410.14966
Autor:
Feng, Shiwei, Chen, Xuan, Cheng, Zhiyuan, Xiong, Zikang, Gao, Yifei, Cheng, Siyuan, Kate, Sayali, Zhang, Xiangyu
Robot navigation is increasingly crucial across applications like delivery services and warehouse management. The integration of Reinforcement Learning (RL) with classical planning has given rise to meta-planners that combine the adaptability of RL w
Externí odkaz:
http://arxiv.org/abs/2409.10832
Autor:
Feng, Shiwei, Ye, Yapeng, Shi, Qingkai, Cheng, Zhiyuan, Xu, Xiangzhe, Cheng, Siyuan, Choi, Hongjun, Zhang, Xiangyu
As Autonomous driving systems (ADS) have transformed our daily life, safety of ADS is of growing significance. While various testing approaches have emerged to enhance the ADS reliability, a crucial gap remains in understanding the accidents causes.
Externí odkaz:
http://arxiv.org/abs/2409.07774
Monocular Depth Estimation (MDE) plays a vital role in applications such as autonomous driving. However, various attacks target MDE models, with physical attacks posing significant threats to system security. Traditional adversarial training methods,
Externí odkaz:
http://arxiv.org/abs/2406.05857
Autor:
Li, Dengchun, Ma, Yingzi, Wang, Naizheng, Ye, Zhengmao, Cheng, Zhiyuan, Tang, Yinghao, Zhang, Yan, Duan, Lei, Zuo, Jie, Yang, Cal, Tang, Mingjie
Fine-tuning Large Language Models (LLMs) is a common practice to adapt pre-trained models for specific applications. While methods like LoRA have effectively addressed GPU memory constraints during fine-tuning, their performance often falls short, es
Externí odkaz:
http://arxiv.org/abs/2404.15159
Autor:
Cheng, Zhiyuan, Liu, Zhaoyi, Guo, Tengda, Feng, Shiwei, Liu, Dongfang, Tang, Mingjie, Zhang, Xiangyu
Pixel-wise regression tasks (e.g., monocular depth estimation (MDE) and optical flow estimation (OFE)) have been widely involved in our daily life in applications like autonomous driving, augmented reality and video composition. Although certain appl
Externí odkaz:
http://arxiv.org/abs/2404.00924
Autor:
Lao, Jiale, Wang, Yibo, Li, Yufei, Wang, Jianping, Zhang, Yunjia, Cheng, Zhiyuan, Chen, Wanghu, Tang, Mingjie, Wang, Jianguo
Modern database management systems (DBMS) expose hundreds of configurable knobs to control system behaviours. Determining the appropriate values for these knobs to improve DBMS performance is a long-standing problem in the database community. As ther
Externí odkaz:
http://arxiv.org/abs/2311.03157
Autor:
Cheng, Zhiyuan, Choi, Hongjun, Liang, James, Feng, Shiwei, Tao, Guanhong, Liu, Dongfang, Zuzak, Michael, Zhang, Xiangyu
Multi-sensor fusion (MSF) is widely used in autonomous vehicles (AVs) for perception, particularly for 3D object detection with camera and LiDAR sensors. The purpose of fusion is to capitalize on the advantages of each modality while minimizing its w
Externí odkaz:
http://arxiv.org/abs/2304.14614
Monocular Depth Estimation (MDE) is a critical component in applications such as autonomous driving. There are various attacks against MDE networks. These attacks, especially the physical ones, pose a great threat to the security of such systems. Tra
Externí odkaz:
http://arxiv.org/abs/2301.13487