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of 46
pro vyhledávání: '"Pan, Jinsheng"'
Autor:
Wang, Jiongxiao, Wu, Fangzhou, Li, Wendi, Pan, Jinsheng, Suh, Edward, Mao, Z. Morley, Chen, Muhao, Xiao, Chaowei
Large language models (LLMs) have been widely deployed as the backbone with additional tools and text information for real-world applications. However, integrating external information into LLM-integrated applications raises significant security conc
Externí odkaz:
http://arxiv.org/abs/2410.21492
Recent advances show that two-stream approaches have achieved outstanding performance in hateful meme detection. However, hateful memes constantly evolve as new memes emerge by fusing progressive cultural ideas, making existing methods obsolete or in
Externí odkaz:
http://arxiv.org/abs/2407.21004
Autor:
Lyu, Hanjia, Huang, Jinfa, Zhang, Daoan, Yu, Yongsheng, Mou, Xinyi, Pan, Jinsheng, Yang, Zhengyuan, Wei, Zhongyu, Luo, Jiebo
Recent research has offered insights into the extraordinary capabilities of Large Multimodal Models (LMMs) in various general vision and language tasks. There is growing interest in how LMMs perform in more specialized domains. Social media content,
Externí odkaz:
http://arxiv.org/abs/2311.07547
Understanding the framing of political issues is of paramount importance as it significantly shapes how individuals perceive, interpret, and engage with these matters. While prior research has independently explored framing within news media and by s
Externí odkaz:
http://arxiv.org/abs/2309.09508
Autor:
Tong, Richard Jiarui, Cao, Cassie Chen, Lee, Timothy Xueqian, Zhao, Guodong, Wan, Ray, Wang, Feiyue, Hu, Xiangen, Schmucker, Robin, Pan, Jinsheng, Quevedo, Julian, Lu, Yu
This paper presents the Never Ending Open Learning Adaptive Framework (NEOLAF), an integrated neural-symbolic cognitive architecture that models and constructs intelligent agents. The NEOLAF framework is a superior approach to constructing intelligen
Externí odkaz:
http://arxiv.org/abs/2308.03990
As AI systems become increasingly prevalent in various aspects of daily life, gaining a comprehensive understanding of public perception towards these AI systems has become increasingly essential for several reasons such as ethical considerations, us
Externí odkaz:
http://arxiv.org/abs/2307.05809
There is a broad consensus that news media outlets incorporate ideological biases in their news articles. However, prior studies on measuring the discrepancies among media outlets and further dissecting the origins of thematic differences suffer from
Externí odkaz:
http://arxiv.org/abs/2303.15708
We first adopt a human-guided machine learning framework to develop a new dataset for hyperpartisan news title detection with 2,200 manually labeled and 1.8 million machine-labeled titles that were posted from 2014 to the present by nine representati
Externí odkaz:
http://arxiv.org/abs/2301.06270
Publikováno v:
In Telematics and Informatics August 2024 92
Akademický článek
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