Facts about zhang yiming

AMONG the facts TikTok’s lawsuit against the US government surfaced: billionaire ByteDance founder Zhang Yiming is living in Singapore while keeping Chinese citizenship.Zhang joins a raft of corporate chieftains who’ve relocated to the island state after years of regulatory tightening and Covid restrictions hammered China’s once free-wheeling tech sector. Fellow entrepreneurs with close ties to the Asian financial hub include Alibaba Group Holding chief executive officer Eddie Wu — who is a naturalised Singaporean citizen — and crypto pioneer Wu Jihan.Zhang is a Chinese national residing in Singapore who now owns roughly 21 per cent of TikTok’s parent, ByteDance said in its lawsuit challenging the TikTok divest-or-ban law. Global investors and ByteDance employees own the rest.The billionaire spent much of 2022 overseas, using Singapore as a primary base, the Information reported at the time, fueling speculation he has applied for foreign citizenship. TikTok included Zhang’s status in a section outlining influential figures at the company.Like many of China’s corporate elite, several of ByteDance’s honchos have shown a predilection for the prosperous city state in past years. BT in your inboxStart and end each day with the latest news stories and analyses delivered straight to your inbox.Zhang years ago handed leadership at ByteDance to fellow co-founder and college roommate Liang Rubo, who’s now also based there. TikTok CEO Shou Chew himself is Singaporean. Other senior executives for ByteDance’s Chinese operations, including commercialisation chief Zhang Lidong, remain in their home country.Zhang’s 21 per cent slice of ByteDance is worth more than US$40 billion, based on the company’s US$268 billion valuation during a recent share buyback programme. The filing also shows Zhang has held onto his shares over the past year, since TikTok’s CEO revealed his boss’s stake of around 20 per cent during a Congressional hearing.Zhang’s current status emerged after TikTok filed a lawsuit against legislation requiring ByteDance to hive off its most successful global invention. The bill sailed through Congress and President Joe Biden signed into law in April, beginning a 270-day countdown for a sale or a US prohibition of the popular video-sharing platform.The lawsuit affirms expectations that ByteDance doesn’t intend to find a buyer for TikTok as the deadline approaches. Instead, the Chinese firm wants the law declared unconstitutional, saying it violates the First Amendment. BLOOMBERG

Image source, Getty ImagesImage caption, TikTok chief executive Shou Zi Chew is expected to face aggressive questioning from US lawmakersAuthor, Nicholas YongRole, BBC News, Singapore22 March 2023Amid growing global suspicion of TikTok that may lead to a US ban of the Chinese app, the spotlight has now fallen on its enigmatic chief executive Shou Zi Chew.The 40-year-old Singaporean will testify before the US House Energy and Commerce Committee on Thursday about the app's data security and privacy practices, and its alleged ties to Beijing. Little is known about the way he operates or even how much power he truly holds at the company. Chief operating officer Vanessa Pappas has been the public face of TikTok, and was grilled by Congress last September about US data flows to China.A New York Times profile last September, citing former TikTok and ByteDance executives, also suggested that Mr Chew's ability to make decisions is limited, and that ByteDance founder Zhang Yiming holds the reins at the company.Video caption, Watch: The fight over TikTok explained in 60 secondsBut TikTok is now putting Mr Chew front and centre publicly, at a time when TikTok's connections to the Chinese government are under great scrutiny. In a letter to lawmakers last June stressing that it operates autonomously of parent company ByteDance, the company took pains to note that he is not from China but "a Singaporean based in Singapore".Born and raised in the city state, he attended an elite school with a strong Chinese heritage and is fluent

Yao, Zhen Bi, Shumin Deng. [Github] [Google Drive] [Baidu Pan]Editing Large Language Models, AACL 2023 Tutorial Ningyu Zhang, Yunzhi Yao, Shumin Deng. [Github] [Google Drive] [Baidu Pan]SurveysKnowledge Mechanisms in Large Language Models: A Survey and Perspective (EMNLP 2024 Findings) Mengru Wang, Yunzhi Yao, Ziwen Xu, Shuofei Qiao, Shumin Deng, Peng Wang, Xiang Chen, Jia-Chen Gu, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen, Ningyu Zhang. [paper]A Comprehensive Study of Knowledge Editing for Large Language Models Ningyu Zhang, Yunzhi Yao, Bozhong Tian, Peng Wang, Shumin Deng, Mengru Wang, Zekun Xi, Shengyu Mao, Jintian Zhang, Yuansheng Ni, Siyuan Cheng, Ziwen Xu, Xin Xu, Jia-Chen Gu, Yong Jiang, Pengjun Xie, Fei Huang, Lei Liang, Zhiqiang Zhang, Xiaowei Zhu, Jun Zhou, Huajun Chen.[paper][benchmark][code]Editing Large Language Models: Problems, Methods, and Opportunities, EMNLP 2023 Main Conference Paper Yunzhi Yao, Peng Wang, Bozhong Tian, Siyuan Cheng, Zhoubo Li, Shumin Deng, Huajun Chen, Ningyu Zhang. [paper][code]Knowledge Editing for Large Language Models: A Survey Song Wang, Yaochen Zhu, Haochen Liu, Zaiyi Zheng, Chen Chen, Jundong Li. [paper]A Survey on Knowledge Editing of Neural Networks Vittorio Mazzia, Alessandro Pedrani, Andrea Caciolai, Kay Rottmann, Davide Bernardi. [paper]Knowledge Unlearning for LLMs: Tasks, Methods, and Challenges Nianwen Si, Hao Zhang, Heyu Chang, Wenlin Zhang, Dan Qu, Weiqiang Zhang. [paper]MethodsPreserve ParametersMemory-basedMemory-Based Model Editing at Scale (ICML 2022) Eric Mitchell, Charles Lin, Antoine Bosselut, Christopher D. Manning, Chelsea Finn.[paper] [code] [demo]Fixing Model Bugs with Natural Language Patches. (EMNLP 2022) Shikhar Murty, Christopher D. Manning, Scott M. Lundberg, Marco Túlio Ribeiro.[paper] [code]MemPrompt: Memory-assisted Prompt Editing with User Feedback. (EMNLP 2022) Aman Madaan, Niket Tandon, Peter Clark, Yiming Yang.[paper] [code] [page] [video]Large Language Models with Controllable Working Memory. Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix Yu, Sanjiv Kumar.[paper]Can We Edit Factual Knowledge by In-Context Learning? Ce Zheng, Lei Li, Qingxiu Dong, Yuxuan Fan, Zhiyong Wu, Jingjing Xu, Baobao Chang.[paper]Can LMs Learn New Entities from Descriptions? Challenges in Propagating Injected Knowledge Yasumasa Onoe, Michael J.Q. Zhang, Shankar Padmanabhan, Greg Durrett, Eunsol Choi.[paper]MQUAKE: Assessing Knowledge Editing inLanguage Models via Multi-Hop Questions Zexuan Zhong, Zhengxuan Wu, Christopher D. Manning, Christopher Potts, Danqi Chen.[paper] [code]PokeMQA: Programmable knowledge editing for Multi-hop Question Answering Hengrui Gu, Kaixiong Zhou, Xiaotian Han, Ninghao Liu, Ruobing Wang, Xin Wang. [paper] [code]Retrieval-augmented Multilingual Knowledge Editing Weixuan Wang, Barry Haddow, Alexandra Birch.[paper] [code]MEMORYLLM: Towards Self-Updatable Large Language Models Yu Wang, Xiusi Chen, Jingbo Shang, Julian McAuley. [paper]DeepEdit: Knowledge Editing as Decoding with Constraints Yiwei Wang,Muhao Chen,Nanyun Peng, Kai-Wei Chang. [paper]Stable Knowledge Editing in Large Language Models. Zihao Wei,Liang Pang,Hanxing Ding,Jingcheng Deng,Huawei Shen,Xueqi Cheng. [paper]Knowledge Editing on Black-box Large Language Models. Xiaoshuai Song, Zhengyang Wang, Keqing He, Guanting Dong, Jinxu Zhao, Weiran Xu. [paper]Learning to Edit: Aligning LLMs with Knowledge Editing. Yuxin Jiang, Yufei Wang, Chuhan Wu, Wanjun Zhong, Xingshan Zeng, Jiahui Gao, Liangyou Li, Xin Jiang, Lifeng Shang, Ruiming Tang, Qun Liu, Wei Wang. [paper]Robust and Scalable Model Editing for Large Language Models. Yingfa Chen, Zhengyan Zhang, Xu Han, Chaojun Xiao, Zhiyuan Liu, Chen Chen, Kuai Li, Tao Yang, Maosong Sun.

Liu, Joseph Bae, Junjun He, Dimitris Samaras, Prateek Prasanna.Self Pre-training with Masked Autoencoders for Medical Image Analysis. [ArXiv'2022]SD-MAE: Yang Luo, Zhineng Chen, Xieping Gao.Self-distillation Augmented Masked Autoencoders for Histopathological Image Classification. [ArXiv'2022]GCMAE: Hao Quan, Xingyu Li, Weixing Chen, Qun Bai, Mingchen Zou, Ruijie Yang, Tingting Zheng, Ruiqun Qi, Xinghua Gao, Xiaoyu Cui.Global Contrast Masked Autoencoders Are Powerful Pathological Representation Learners. [ArXiv'2022] [code]FreMAE: Wenxuan Wang, Jing Wang, Chen Chen, Jianbo Jiao, Lichao Sun, Yuanxiu Cai, Shanshan Song, Jiangyun Li.FreMAE: Fourier Transform Meets Masked Autoencoders for Medical Image Segmentation. [ArXiv'2023]3DMIM_Medical: Zekai Chen, Devansh Agarwal, Kshitij Aggarwal, Wiem Safta, Samit Hirawat, Venkat Sethuraman, Mariann Micsinai Balan, Kevin Brown.Masked Image Modeling Advances 3D Medical Image Analysis. [WACV'2023] [code]Face RecognitionFaceMAE: Kai Wang, Bo Zhao, Xiangyu Peng, Zheng Zhu, Jiankang Deng, Xinchao Wang, Hakan Bilen, Yang You.FaceMAE: Privacy-Preserving Face Recognition via Masked Autoencoders. [ArXiv'2022] [code]Scene Text Recognition (OCR)MaskOCR: Pengyuan Lyu, Chengquan Zhang, Shanshan Liu, Meina Qiao, Yangliu Xu, Liang Wu, Kun Yao, Junyu Han, Errui Ding, Jingdong Wang.MaskOCR: Text Recognition with Masked Encoder-Decoder Pretraining. [ArXiv'2022]DocMAE: Shaokai Liu, Hao Feng, Wengang Zhou, Houqiang Li, Cong Liu, Feng Wu.DocMAE: Document Image Rectification via Self-supervised Representation Learning. [ICME'2023]Remote Sensing ImageSatMAE: Yezhen Cong, Samar Khanna, Chenlin Meng, Patrick Liu, Erik Rozi, Yutong He, Marshall Burke, David B. Lobell, Stefano Ermon.SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery. [ArXiv'2022]CMID: Dilxat Muhtar, Xueliang Zhang, Pengfeng Xiao, Zhenshi Li, Feng Gu.CMID: A Unified Self-Supervised Learning Framework for Remote Sensing Image Understanding. [TGRS'2023] [code]3D Point CloudPointBERT: Xumin Yu, Lulu Tang, Yongming Rao, Tiejun Huang, Jie Zhou, Jiwen Lu.Pre-Training 3D Point Cloud Transformers with Masked Point Modeling. [CVPR'2022] [code]PointMAE: Yatian Pang, Wenxiao Wang, Francis E.H. Tay, Wei Liu, Yonghong Tian, Li Yuan.Masked Autoencoders for Point Cloud Self-supervised Learning. [ECCV'2022] [code]MaskPoint: Haotian Liu, Mu Cai, Yong Jae Lee.Masked Discrimination for Self-Supervised Learning on Point Clouds. [ECCV'2022] [code]MeshMAE: Yaqian Liang, Shanshan Zhao, Baosheng Yu, Jing Zhang, Fazhi He.MeshMAE: Masked Autoencoders for 3D Mesh Data Analysis. [ECCV'2022]VoxelMAE: Chen Min, Xinli Xu, Dawei Zhao, Liang Xiao, Yiming Nie, Bin Dai.Voxel-MAE: Masked Autoencoders for Pre-training Large-scale Point Clouds. [ArXiv'2022]Point-M2AE: Renrui Zhang, Ziyu Guo, Peng Gao, Rongyao Fang, Bin Zhao, Dong Wang, Yu Qiao, Hongsheng Li.Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training. [NIPS'2022] [code]I2P-MAE: Renrui Zhang, Liuhui Wang, Yu Qiao, Peng Gao, Hongsheng Li.Learning 3D Representations from 2D Pre-trained Models viaImage-to-Point Masked Autoencoders. [CVPR'2023] [code]ACT: Runpei Dong, Zekun Qi, Linfeng Zhang, Junbo Zhang, Jianjian Sun, Zheng Ge, Li Yi, Kaisheng Ma.Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?. [ICLR'2023] [code]ReCon: Zekun Qi, Runpei Dong, Guofan Fan, Zheng Ge, Xiangyu Zhang, Kaisheng Ma, Li Yi.Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining. [ICML'2023] [code]Reinforcement LearningMLR: Tao Yu, Zhizheng Zhang, Cuiling Lan, Yan Lu, Zhibo Chen.Mask-based Latent Reconstruction for Reinforcement Learning. [ArXiv'2022]AudioMAM: Junkun Chen, Mingbo Ma, Renjie Zheng, Liang Huang.MAM: Masked Acoustic Modeling for End-to-End Speech-to-Text Translation. [ArXiv'2021]MAE-AST: Alan Baade, Puyuan Peng, David Harwath.MAE-AST: Masked Autoencoding Audio Spectrogram Transformer. [ArXiv'2022] [code]MaskSpec: Dading Chong, Helin Wang, Peilin Zhou, Qingcheng Zeng.Masked Spectrogram Prediction For

Example, a child could get mono from sharing a water bottle with a sick friend. Children with mono won't start feeling sick for four to six weeks after they've caught the virus. Once they start feeling unwell, the symptoms of mono can last anywhere from two weeks to over a month. A child with mono is contagious for at least as long as they have symptoms, which can last for months. That said, some never develop symptoms but are still contagious.Verywell Health uses only high-quality sources, including peer-reviewed studies, to support the facts within our articles. Read our editorial process to learn more about how we fact-check and keep our content accurate, reliable, and trustworthy. Boston Children’s Hospital. Infectious mononucleosis. Centers for Disease Control and Prevention. About Epstein-Barr virus (EBV).Nemours Children's Health. How Long Is Mono Contagious?.American Academy of Pediatrics. Mononucleosis.Wu Y, Ma S, Zhang L, Zu D, Gu F, Ding X, Zhang L. Clinical manifestations and laboratory results of 61 children with infectious mononucleosis. J Int Med Res. 2020;48(10):300060520924550. doi:10.1177/0300060520924550Nemours Children's Health. Mononucleosis (Mono).Centers for Disease Control and Prevention (CDC). About Infectious Mononucleosis.Nationwide Children's. Mononucleosis (Infectious).By Carrie Madormo, RN, MPHMadormo is a health writer with over a decade of experience as a registered nurse. She has worked in pediatrics, oncology, chronic pain, and public health.Thanks for your feedback!