Zobrazeno 1 - 10
of 2 522
pro vyhledávání: '"Li, Lijun"'
Publikováno v:
IEEE Robotics and Automation Letters, vol. 9, no. 6, pp. 5134-5141, June 2024
A common prerequisite for evaluating a visual(-inertial) odometry (VO/VIO) algorithm is to align the timestamps and the reference frame of its estimated trajectory with a reference ground-truth derived from a system of superior precision, such as a m
Externí odkaz:
http://arxiv.org/abs/2404.14894
We study a public event scheduling problem, where multiple public events are scheduled to coordinate the availability of multiple agents. The availability of each agent is determined by solving a separate flexible interval job scheduling problem, whe
Externí odkaz:
http://arxiv.org/abs/2404.11879
Publikováno v:
Information Fusion 2024
As the concept of Industries 5.0 develops, industrial metaverses are expected to operate in parallel with the actual industrial processes to offer ``Human-Centric" Safe, Secure, Sustainable, Sensitive, Service, and Smartness ``6S" manufacturing solut
Externí odkaz:
http://arxiv.org/abs/2404.07476
Autor:
Shi, Zhelun, Wang, Zhipin, Fan, Hongxing, Zhang, Zaibin, Li, Lijun, Zhang, Yongting, Yin, Zhenfei, Sheng, Lu, Qiao, Yu, Shao, Jing
Large Language Models (LLMs) aim to serve as versatile assistants aligned with human values, as defined by the principles of being helpful, honest, and harmless (hhh). However, in terms of Multimodal Large Language Models (MLLMs), despite their comme
Externí odkaz:
http://arxiv.org/abs/2403.17830
Autor:
Zhou, Weikang, Wang, Xiao, Xiong, Limao, Xia, Han, Gu, Yingshuang, Chai, Mingxu, Zhu, Fukang, Huang, Caishuang, Dou, Shihan, Xi, Zhiheng, Zheng, Rui, Gao, Songyang, Zou, Yicheng, Yan, Hang, Le, Yifan, Wang, Ruohui, Li, Lijun, Shao, Jing, Gui, Tao, Zhang, Qi, Huang, Xuanjing
Jailbreak attacks are crucial for identifying and mitigating the security vulnerabilities of Large Language Models (LLMs). They are designed to bypass safeguards and elicit prohibited outputs. However, due to significant differences among various jai
Externí odkaz:
http://arxiv.org/abs/2403.12171
Autor:
Li, Lijun, Dong, Bowen, Wang, Ruohui, Hu, Xuhao, Zuo, Wangmeng, Lin, Dahua, Qiao, Yu, Shao, Jing
In the rapidly evolving landscape of Large Language Models (LLMs), ensuring robust safety measures is paramount. To meet this crucial need, we propose \emph{SALAD-Bench}, a safety benchmark specifically designed for evaluating LLMs, attack, and defen
Externí odkaz:
http://arxiv.org/abs/2402.05044
Autor:
Lu, Chaochao, Qian, Chen, Zheng, Guodong, Fan, Hongxing, Gao, Hongzhi, Zhang, Jie, Shao, Jing, Deng, Jingyi, Fu, Jinlan, Huang, Kexin, Li, Kunchang, Li, Lijun, Wang, Limin, Sheng, Lu, Chen, Meiqi, Zhang, Ming, Ren, Qibing, Chen, Sirui, Gui, Tao, Ouyang, Wanli, Wang, Yali, Teng, Yan, Wang, Yaru, Wang, Yi, He, Yinan, Wang, Yingchun, Wang, Yixu, Zhang, Yongting, Qiao, Yu, Shen, Yujiong, Mou, Yurong, Chen, Yuxi, Zhang, Zaibin, Shi, Zhelun, Yin, Zhenfei, Wang, Zhipin
Multi-modal Large Language Models (MLLMs) have shown impressive abilities in generating reasonable responses with respect to multi-modal contents. However, there is still a wide gap between the performance of recent MLLM-based applications and the ex
Externí odkaz:
http://arxiv.org/abs/2401.15071
Autor:
Zhang, Zaibin, Zhang, Yongting, Li, Lijun, Gao, Hongzhi, Wang, Lijun, Lu, Huchuan, Zhao, Feng, Qiao, Yu, Shao, Jing
Multi-agent systems, when enhanced with Large Language Models (LLMs), exhibit profound capabilities in collective intelligence. However, the potential misuse of this intelligence for malicious purposes presents significant risks. To date, comprehensi
Externí odkaz:
http://arxiv.org/abs/2401.11880
Autor:
Shen, Huijun, Chen, Guo, Li, Bojie, Lin, Xingtong, Zhang, Xingyu, Wang, Xizheng, Geron, Amit, Rabinovitch, Shamir, Lin, Haifeng, Ruan, Han, Li, Lijun, Zhou, Jingbin, Tan, Kun
Remote Direct Memory Access (RDMA) has been haunted by the need of pinning down memory regions. Pinning limits the memory utilization because it impedes on-demand paging and swapping. It also increases the initialization latency of large memory appli
Externí odkaz:
http://arxiv.org/abs/2310.11062
The current interacting hand (IH) datasets are relatively simplistic in terms of background and texture, with hand joints being annotated by a machine annotator, which may result in inaccuracies, and the diversity of pose distribution is limited. How
Externí odkaz:
http://arxiv.org/abs/2309.09301