Zobrazeno 1 - 10
of 610
pro vyhledávání: '"Liu Jianyi"'
Autor:
Sun, Fei, Ren, Jianhua, Li, Hongfang, Wu, Yiwei, Liang, Jianwei, Yang, Hui, Zhang, Yi, Liu, Jianyi, Liu, Linjie, Wu, Mengjun, Zhang, Xiaoyue, Zhu, Wenpeng, Chen, Weijin, Zheng, Yue
Topological textures like vortices, labyrinths and skyrmions formed in ferroic materials have attracted extensive interests during the past decade for their fundamental physics, intriguing topology, and technological prospects. So far, polar skyrmion
Externí odkaz:
http://arxiv.org/abs/2409.14843
With the evolution of generative linguistic steganography techniques, conventional steganalysis falls short in robustly quantifying the alterations induced by steganography, thereby complicating detection. Consequently, the research paradigm has pivo
Externí odkaz:
http://arxiv.org/abs/2409.01780
Image anti-forensics is a critical topic in the field of image privacy and security research. With the increasing ease of manipulating or generating human faces in images, the potential misuse of such forged images is a growing concern. This study ai
Externí odkaz:
http://arxiv.org/abs/2408.11365
Autor:
Yang, Zhen, Wang, Wenhui, Qi, Tao, Zhang, Peng, Zhang, Tianyun, Zhang, Ru, Liu, Jianyi, Huang, Yongfeng
Accurately recommending candidate news articles to users has always been the core challenge of news recommendation system. News recommendations often require modeling of user interest to match candidate news. Recent efforts have primarily focused on
Externí odkaz:
http://arxiv.org/abs/2408.00859
To detect stego (steganographic text) in complex scenarios, linguistic steganalysis (LS) with various motivations has been proposed and achieved excellent performance. However, with the development of generative steganography, some stegos have strong
Externí odkaz:
http://arxiv.org/abs/2406.04218
Currently, most methods for text steganalysis are based on deep neural networks (DNNs). However, in real-life scenarios, obtaining a sufficient amount of labeled stego-text for correctly training networks using a large number of parameters is often c
Externí odkaz:
http://arxiv.org/abs/2406.18565
While Large Language Models (LLMs) demonstrate exceptional performance in a multitude of Natural Language Processing (NLP) tasks, they encounter challenges in practical applications, including issues with hallucinations, inadequate knowledge updating
Externí odkaz:
http://arxiv.org/abs/2402.04978
Linguistic steganography (LS) tasks aim to generate steganographic text (stego) based on secret. Only authorized receivers can perceive and extract secrets, thereby protecting privacy. However, existing generative LS schemes often do not consider the
Externí odkaz:
http://arxiv.org/abs/2401.15656
Linguistic steganalysis (LS) tasks aim to detect whether a text contains secret information. Existing LS methods focus on the deep-learning model design and they achieve excellent results in ideal data. However, they overlook the unique user characte
Externí odkaz:
http://arxiv.org/abs/2311.01775
Autor:
Liu, Jianyi1 (AUTHOR), Luo, Fuqun1 (AUTHOR), Guo, Yizhi1 (AUTHOR), Li, Yandeng1 (AUTHOR), Jiang, Chao1 (AUTHOR), Pi, Zhendong1 (AUTHOR), Luo, Jie1 (AUTHOR), Long, Zhiyuan1 (AUTHOR), Wen, Jun1 (AUTHOR) Cdwenjun1973@163.com, Huang, Zhihua1 (AUTHOR) hzhgyb@163.com, Zhu, Jianming1 (AUTHOR) Zhujm0718@126.com
Publikováno v:
Scientific Reports. 11/9/2024, p1-10. 10p.
