Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent

Autor: Sun, Xingwu, Chen, Yanfeng, Huang, Yiqing, Xie, Ruobing, Zhu, Jiaqi, Zhang, Kai, Li, Shuaipeng, Yang, Zhen, Han, Jonny, Shu, Xiaobo, Bu, Jiahao, Chen, Zhongzhi, Huang, Xuemeng, Lian, Fengzong, Yang, Saiyong, Yan, Jianfeng, Zeng, Yuyuan, Ren, Xiaoqin, Yu, Chao, Wu, Lulu, Mao, Yue, Xia, Jun, Yang, Tao, Zheng, Suncong, Wu, Kan, Jiao, Dian, Xue, Jinbao, Zhang, Xipeng, Wu, Decheng, Liu, Kai, Wu, Dengpeng, Xu, Guanghui, Chen, Shaohua, Chen, Shuang, Feng, Xiao, Hong, Yigeng, Zheng, Junqiang, Xu, Chengcheng, Li, Zongwei, Kuang, Xiong, Hu, Jianglu, Chen, Yiqi, Deng, Yuchi, Li, Guiyang, Liu, Ao, Zhang, Chenchen, Hu, Shihui, Zhao, Zilong, Wu, Zifan, Ding, Yao, Wang, Weichao, Liu, Han, Wang, Roberts, Fei, Hao, Yu, Peijie, Zhao, Ze, Cao, Xun, Wang, Hai, Xiang, Fusheng, Huang, Mengyuan, Xiong, Zhiyuan, Hu, Bin, Hou, Xuebin, Jiang, Lei, Ma, Jianqiang, Wu, Jiajia, Deng, Yaping, Shen, Yi, Wang, Qian, Liu, Weijie, Liu, Jie, Chen, Meng, Dong, Liang, Jia, Weiwen, Chen, Hu, Liu, Feifei, Yuan, Rui, Xu, Huilin, Yan, Zhenxiang, Cao, Tengfei, Hu, Zhichao, Feng, Xinhua, Du, Dong, Yu, Tinghao, Tao, Yangyu, Zhang, Feng, Zhu, Jianchen, Xu, Chengzhong, Li, Xirui, Zha, Chong, Ouyang, Wen, Xia, Yinben, Li, Xiang, He, Zekun, Chen, Rongpeng, Song, Jiawei, Chen, Ruibin, Jiang, Fan, Zhao, Chongqing, Wang, Bo, Gong, Hao, Gan, Rong, Hu, Winston, Kang, Zhanhui, Yang, Yong, Liu, Yuhong, Wang, Di, Jiang, Jie

In this paper, we introduce Hunyuan-Large, which is currently the largest open-source Transformer-based mixture of experts model, with a total of 389 billion parameters and 52 billion activation parameters, capable of handling up to 256K tokens. We c

Externí odkaz: http://arxiv.org/abs/2411.02265

Defensive Reconfigurable Intelligent Surface (D-RIS) Based on Non-Reciprocal Channel Links

Autor: Chen-Hu, Kun, Popovski, Petar

Publikováno v: IEEE Transactions on Communications 2024

A reconfigurable intelligent surface (RIS) is commonly made of low-cost passive and reflective meta-materials with excellent beam steering capabilities. It is applied to enhance wireless communication systems as a customizable signal reflector. Howev

Externí odkaz: http://arxiv.org/abs/2407.04905

Diffusion Posterior Proximal Sampling for Image Restoration

Autor: Wu, Hongjie, He, Linchao, Zhang, Mingqin, Chen, Dongdong, Luo, Kunming, Luo, Mengting, Zhou, Ji-Zhe, Chen, Hu, Lv, Jiancheng

Diffusion models have demonstrated remarkable efficacy in generating high-quality samples. Existing diffusion-based image restoration algorithms exploit pre-trained diffusion models to leverage data priors, yet they still preserve elements inherited

Externí odkaz: http://arxiv.org/abs/2402.16907

Proposals for ruling out the real quantum theories in an entanglement-swapping quantum network with causally independent sources

Autor: Yao, Jian, Chen, Hu, Mao, Ya-Li, Li, Zheng-Da, Fan, Jingyun

The question of whether complex numbers play a fundamental role in quantum theory has been debated since the inception of quantum mechanics. Recently, a feasible proposal to differentiate between real and complex quantum theories based on the techniq

Externí odkaz: http://arxiv.org/abs/2312.14547

Machine learning discrimination of Gleason scores below GG3 and above GG4 for HSPC patients diagnosis

Autor: Bingyu Zhu, Longguo Dai, Huijian Wang, Kun Zhang, Chongjian Zhang, Yang Wang, Feiyu Yin, Ji Li, Enfa Ning, Qilin Wang, Libo Yang, Hong Yang, Ruiqian Li, Jun Li, Chen Hu, Hongyi Wu, Haiyang Jiang, Yu Bai

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)

Abstract This study aims to develop machine learning (ML)-assisted models for analyzing datasets related to Gleason scores in prostate cancer, conducting statistical analyses on the datasets, and identifying meaningful features. We retrospectively co

Externí odkaz: https://doaj.org/article/f834aacd378242aea95d39f1ae2b4974