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pro vyhledávání: '"Zhan, Chenlu"'
Autor:
Zhang, Hanrong, Huang, Jingyuan, Mei, Kai, Yao, Yifei, Wang, Zhenting, Zhan, Chenlu, Wang, Hongwei, Zhang, Yongfeng
Although LLM-based agents, powered by Large Language Models (LLMs), can use external tools and memory mechanisms to solve complex real-world tasks, they may also introduce critical security vulnerabilities. However, the existing literature does not c
Externí odkaz:
http://arxiv.org/abs/2410.02644
Autor:
Zhang, Hanrong, Wang, Zhenting, Han, Tingxu, Jin, Mingyu, Zhan, Chenlu, Du, Mengnan, Wang, Hongwei, Ma, Shiqing
Self-supervised learning models are vulnerable to backdoor attacks. Existing backdoor attacks that are effective in self-supervised learning often involve noticeable triggers, like colored patches, which are vulnerable to human inspection. In this pa
Externí odkaz:
http://arxiv.org/abs/2405.14672
Medical generative models, acknowledged for their high-quality sample generation ability, have accelerated the fast growth of medical applications. However, recent works concentrate on separate medical generation models for distinct medical tasks and
Externí odkaz:
http://arxiv.org/abs/2403.04290
Medical vision-language pre-training (Med-VLP) models have recently accelerated the fast-growing medical diagnostics application. However, most Med-VLP models learn task-specific representations independently from scratch, thereby leading to great in
Externí odkaz:
http://arxiv.org/abs/2312.11171
Autor:
Wang, Zixuan, Qin, Bo, Li, Mengxuan, Zhan, Chenlu, Butala, Mark D., Peng, Peng, Wang, Hongwei
The efficient utilization of wind power by wind turbines relies on the ability of their pitch systems to adjust blade pitch angles in response to varying wind speeds. However, the presence of multiple health conditions in the pitch system due to the
Externí odkaz:
http://arxiv.org/abs/2306.14701
Medical Visual Question Answering (Medical-VQA) aims to to answer clinical questions regarding radiology images, assisting doctors with decision-making options. Nevertheless, current Medical-VQA models learn cross-modal representations through residi
Externí odkaz:
http://arxiv.org/abs/2212.10729
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