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On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective

Fuente: arXiv

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Bibliographic Details
Main Authors:	Huang, Yue, Gao, Chujie, Wu, Siyuan, Wang, Haoran, Wang, Xiangqi, Zhou, Yujun, Wang, Yanbo, Ye, Jiayi, Shi, Jiawen, Zhang, Qihui, Li, Yuan, Bao, Han, Liu, Zhaoyi, Guan, Tianrui, Chen, Dongping, Chen, Ruoxi, Guo, Kehan, Zou, Andy, Kuen-Yew, Bryan Hooi, Xiong, Caiming, Stengel-Eskin, Elias, Zhang, Hongyang, Yin, Hongzhi, Zhang, Huan, Yao, Huaxiu, Yoon, Jaehong, Zhang, Jieyu, Shu, Kai, Zhu, Kaijie, Krishna, Ranjay, Swayamdipta, Swabha, Shi, Taiwei, Shi, Weijia, Li, Xiang, Li, Yiwei, Hao, Yuexing, Jia, Zhihao, Li, Zhize, Chen, Xiuying, Tu, Zhengzhong, Hu, Xiyang, Zhou, Tianyi, Zhao, Jieyu, Sun, Lichao, Huang, Furong, Sasson, Or Cohen, Sattigeri, Prasanna, Reuel, Anka, Lamparth, Max, Zhao, Yue, Dziri, Nouha, Su, Yu, Sun, Huan, Ji, Heng, Xiao, Chaowei, Bansal, Mohit, Chawla, Nitesh V., Pei, Jian, Gao, Jianfeng, Backes, Michael, Yu, Philip S., Gong, Neil Zhenqiang, Chen, Pin-Yu, Li, Bo, Song, Dawn, Zhang, Xiangliang
Format:	Preprint
Published:	2025
Subjects:	Computers and Society
Online Access:	Acceder al recurso
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