Zobrazeno 1 - 10
of 66
pro vyhledávání: '"Fang, Zhixuan"'
Most concurrent blockchain systems rely heavily on the Proof-of-Work (PoW) or Proof-of-Stake (PoS) mechanisms for decentralized consensus and security assurance. However, the substantial energy expenditure stemming from computationally intensive yet
Externí odkaz:
http://arxiv.org/abs/2404.09005
Effective action abstraction is crucial in tackling challenges associated with large action spaces in Imperfect Information Extensive-Form Games (IIEFGs). However, due to the vast state space and computational complexity in IIEFGs, existing methods o
Externí odkaz:
http://arxiv.org/abs/2403.04344
Autor:
Xu, Rongwu, Fang, Zhixuan
Cloud deep learning platforms provide cost-effective deep neural network (DNN) training for customers who lack computation resources. However, cloud systems are often untrustworthy and vulnerable to attackers, leading to growing concerns about model
Externí odkaz:
http://arxiv.org/abs/2401.11531
Autor:
Xu, Rongwu, Lin, Brian S., Yang, Shujian, Zhang, Tianqi, Shi, Weiyan, Zhang, Tianwei, Fang, Zhixuan, Xu, Wei, Qiu, Han
Large language models (LLMs) encapsulate vast amounts of knowledge but still remain vulnerable to external misinformation. Existing research mainly studied this susceptibility behavior in a single-turn setting. However, belief can change during a mul
Externí odkaz:
http://arxiv.org/abs/2312.09085
Sharing systems have facilitated the redistribution of underused resources by providing convenient online marketplaces for individual sellers and buyers. However, sellers in these systems may not fully disclose the information of their shared commodi
Externí odkaz:
http://arxiv.org/abs/2308.16320
Autor:
Bhat, Suma, Chen, Canhui, Cheng, Zerui, Fang, Zhixuan, Hebbar, Ashwin, Kannan, Sreeram, Rana, Ranvir, Sheng, Peiyao, Tyagi, Himanshu, Viswanath, Pramod, Wang, Xuechao
Large AI models (e.g., Dall-E, GPT4) have electrified the scientific, technological and societal landscape through their superhuman capabilities. These services are offered largely in a traditional web2.0 format (e.g., OpenAI's GPT4 service). As more
Externí odkaz:
http://arxiv.org/abs/2307.16562
Publikováno v:
IEEE 8th European Symposium on Security and Privacy (EuroS&P), Delft, Netherlands, 2023 pp. 352-372
Single sign-on (SSO) allows users to authenticate to third-party applications through a central identity provider. Despite their wide adoption, deployed SSO systems suffer from privacy problems such as user tracking by the identity provider. While nu
Externí odkaz:
http://arxiv.org/abs/2305.06833
Autor:
Wang, Yujie, Huang, Chao, Yang, Liner, Fang, Zhixuan, Huang, Yaping, Liu, Yang, Yu, Jingsi, Yang, Erhong
This paper introduces a novel crowdsourcing worker selection algorithm, enhancing annotation quality and reducing costs. Unlike previous studies targeting simpler tasks, this study contends with the complexities of label interdependencies in sequence
Externí odkaz:
http://arxiv.org/abs/2305.06683
Proof-of-Work (PoW) consensus mechanism is popular among current blockchain systems, which leads to an increasing concern about the tremendous waste of energy due to massive meaningless computation. To address this issue, we propose a novel and energ
Externí odkaz:
http://arxiv.org/abs/2211.06669
Play-to-earn is one of the prospective categories of decentralized applications. The play-to-earn projects combine blockchain technology with entertaining games and finance, attracting various participants. While huge amounts of capital have been pou
Externí odkaz:
http://arxiv.org/abs/2211.01000