Zobrazeno 1 - 10
of 576
pro vyhledávání: '"Han Xudong"'
Autor:
Mu, Honglin, He, Han, Zhou, Yuxin, Feng, Yunlong, Xu, Yang, Qin, Libo, Shi, Xiaoming, Liu, Zeming, Han, Xudong, Shi, Qi, Zhu, Qingfu, Che, Wanxiang
Large language model (LLM) safety is a critical issue, with numerous studies employing red team testing to enhance model security. Among these, jailbreak methods explore potential vulnerabilities by crafting malicious prompts that induce model output
Externí odkaz:
http://arxiv.org/abs/2410.21083
As large language models (LLMs) advance, their inability to autonomously execute tasks by directly interacting with external tools remains a critical limitation. Traditional methods rely on inputting tool descriptions as context, which is constrained
Externí odkaz:
http://arxiv.org/abs/2410.03439
Autor:
Li, Haonan, Han, Xudong, Wang, Hao, Wang, Yuxia, Wang, Minghan, Xing, Rui, Geng, Yilin, Zhai, Zenan, Nakov, Preslav, Baldwin, Timothy
We introduce Loki, an open-source tool designed to address the growing problem of misinformation. Loki adopts a human-centered approach, striking a balance between the quality of fact-checking and the cost of human involvement. It decomposes the fact
Externí odkaz:
http://arxiv.org/abs/2410.01794
This paper investigates the direct application of standardized designs on the robot for conducting robot hand-eye calibration by employing 3D scanners with collaborative robots. The well-established geometric features of the robot flange are exploite
Externí odkaz:
http://arxiv.org/abs/2407.16041
Autor:
Han, Xudong, Oishi, Nobuyuki, Tian, Yueying, Ucurum, Elif, Young, Rupert, Chatwin, Chris, Birch, Philip
Many Multi-Object Tracking (MOT) approaches exploit motion information to associate all the detected objects across frames. However, many methods that rely on filtering-based algorithms, such as the Kalman Filter, often work well in linear motion sce
Externí odkaz:
http://arxiv.org/abs/2405.15755
Autor:
Lin, Lizhi, Mu, Honglin, Zhai, Zenan, Wang, Minghan, Wang, Yuxia, Wang, Renxi, Gao, Junjie, Zhang, Yixuan, Che, Wanxiang, Baldwin, Timothy, Han, Xudong, Li, Haonan
Generative models are rapidly gaining popularity and being integrated into everyday applications, raising concerns over their safe use as various vulnerabilities are exposed. In light of this, the field of red teaming is undergoing fast-paced growth,
Externí odkaz:
http://arxiv.org/abs/2404.00629
Autor:
Wang, Yuxia, Zhai, Zenan, Li, Haonan, Han, Xudong, Lin, Lizhi, Zhang, Zhenxuan, Zhao, Jingru, Nakov, Preslav, Baldwin, Timothy
Publikováno v:
ACL2024-Findings
Many studies have demonstrated that large language models (LLMs) can produce harmful responses, exposing users to unexpected risks when LLMs are deployed. Previous studies have proposed comprehensive taxonomies of the risks posed by LLMs, as well as
Externí odkaz:
http://arxiv.org/abs/2402.12193
Large language models (LLMs) have achieved success in acting as agents, which interact with environments through tools such as search engines. However, LLMs are optimized for language generation instead of tool use during training or alignment, limit
Externí odkaz:
http://arxiv.org/abs/2402.11651
Autor:
Wang, Renxi, Li, Haonan, Wu, Minghao, Wang, Yuxia, Han, Xudong, Zhang, Chiyu, Baldwin, Timothy
Instruction tuning significantly enhances the performance of large language models (LLMs) across various tasks. However, the procedure to optimizing the mixing of instruction datasets for LLM fine-tuning is still poorly understood. This study categor
Externí odkaz:
http://arxiv.org/abs/2312.10793
Autor:
Guo, Ning, Han, Xudong, Zhong, Shuqiao, Zhou, Zhiyuan, Lin, Jian, Dai, Jian S., Wan, Fang, Song, Chaoyang
This paper presents a novel vision-based proprioception approach for a soft robotic finger that can estimate and reconstruct tactile interactions in both terrestrial and aquatic environments. The key to this system lies in the finger's unique metamat
Externí odkaz:
http://arxiv.org/abs/2312.09863