Zobrazeno 1 - 10
of 7 786
pro vyhledávání: '"Liu, XiaoDong"'
Autor:
DeepSeek-AI, Liu, Aixin, Feng, Bei, Xue, Bing, Wang, Bingxuan, Wu, Bochao, Lu, Chengda, Zhao, Chenggang, Deng, Chengqi, Zhang, Chenyu, Ruan, Chong, Dai, Damai, Guo, Daya, Yang, Dejian, Chen, Deli, Ji, Dongjie, Li, Erhang, Lin, Fangyun, Dai, Fucong, Luo, Fuli, Hao, Guangbo, Chen, Guanting, Li, Guowei, Zhang, H., Bao, Han, Xu, Hanwei, Wang, Haocheng, Zhang, Haowei, Ding, Honghui, Xin, Huajian, Gao, Huazuo, Li, Hui, Qu, Hui, Cai, J. L., Liang, Jian, Guo, Jianzhong, Ni, Jiaqi, Li, Jiashi, Wang, Jiawei, Chen, Jin, Chen, Jingchang, Yuan, Jingyang, Qiu, Junjie, Li, Junlong, Song, Junxiao, Dong, Kai, Hu, Kai, Gao, Kaige, Guan, Kang, Huang, Kexin, Yu, Kuai, Wang, Lean, Zhang, Lecong, Xu, Lei, Xia, Leyi, Zhao, Liang, Wang, Litong, Zhang, Liyue, Li, Meng, Wang, Miaojun, Zhang, Mingchuan, Zhang, Minghua, Tang, Minghui, Li, Mingming, Tian, Ning, Huang, Panpan, Wang, Peiyi, Zhang, Peng, Wang, Qiancheng, Zhu, Qihao, Chen, Qinyu, Du, Qiushi, Chen, R. J., Jin, R. L., Ge, Ruiqi, Zhang, Ruisong, Pan, Ruizhe, Wang, Runji, Xu, Runxin, Zhang, Ruoyu, Chen, Ruyi, Li, S. S., Lu, Shanghao, Zhou, Shangyan, Chen, Shanhuang, Wu, Shaoqing, Ye, Shengfeng, Ma, Shirong, Wang, Shiyu, Zhou, Shuang, Yu, Shuiping, Zhou, Shunfeng, Pan, Shuting, Wang, T., Yun, Tao, Pei, Tian, Sun, Tianyu, Xiao, W. L., Zeng, Wangding, Zhao, Wanjia, An, Wei, Liu, Wen, Liang, Wenfeng, Gao, Wenjun, Yu, Wenqin, Zhang, Wentao, Li, X. Q., Jin, Xiangyue, Wang, Xianzu, Bi, Xiao, Liu, Xiaodong, Wang, Xiaohan, Shen, Xiaojin, Chen, Xiaokang, Zhang, Xiaokang, Chen, Xiaosha, Nie, Xiaotao, Sun, Xiaowen, Wang, Xiaoxiang, Cheng, Xin, Liu, Xin, Xie, Xin, Liu, Xingchao, Yu, Xingkai, Song, Xinnan, Shan, Xinxia, Zhou, Xinyi, Yang, Xinyu, Li, Xinyuan, Su, Xuecheng, Lin, Xuheng, Li, Y. K., Wang, Y. Q., Wei, Y. X., Zhu, Y. X., Zhang, Yang, Xu, Yanhong, Huang, Yanping, Li, Yao, Zhao, Yao, Sun, Yaofeng, Li, Yaohui, Wang, Yaohui, Yu, Yi, Zheng, Yi, Zhang, Yichao, Shi, Yifan, Xiong, Yiliang, He, Ying, Tang, Ying, Piao, Yishi, Wang, Yisong, Tan, Yixuan, Ma, Yiyang, Liu, Yiyuan, Guo, Yongqiang, Wu, Yu, Ou, Yuan, Zhu, Yuchen, Wang, Yuduan, Gong, Yue, Zou, Yuheng, He, Yujia, Zha, Yukun, Xiong, Yunfan, Ma, Yunxian, Yan, Yuting, Luo, Yuxiang, You, Yuxiang, Liu, Yuxuan, Zhou, Yuyang, Wu, Z. F., Ren, Z. Z., Ren, Zehui, Sha, Zhangli, Fu, Zhe, Xu, Zhean, Huang, Zhen, Zhang, Zhen, Xie, Zhenda, Zhang, Zhengyan, Hao, Zhewen, Gou, Zhibin, Ma, Zhicheng, Yan, Zhigang, Shao, Zhihong, Xu, Zhipeng, Wu, Zhiyu, Zhang, Zhongyu, Li, Zhuoshu, Gu, Zihui, Zhu, Zijia, Liu, Zijun, Li, Zilin, Xie, Ziwei, Song, Ziyang, Gao, Ziyi, Pan, Zizheng
We present DeepSeek-V3, a strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token. To achieve efficient inference and cost-effective training, DeepSeek-V3 adopts Multi-head Latent Attention (MLA) an
Externí odkaz:
http://arxiv.org/abs/2412.19437
Autor:
Zeng, Binrui, Ji, Bin, Liu, Xiaodong, Yu, Jie, Li, Shasha, Ma, Jun, Li, Xiaopeng, Wang, Shangwen, Hong, Xinran
As large language models (LLMs) demonstrate exceptional performance across various domains, the deployment of these models on edge devices has emerged as a new trend. Quantization techniques, which reduce the size and memory footprint of LLMs, are ef
Externí odkaz:
http://arxiv.org/abs/2412.18135
Autor:
Zhang, Shaolei, Zhang, Kehao, Fang, Qingkai, Guo, Shoutao, Zhou, Yan, Liu, Xiaodong, Feng, Yang
Large language models (LLMs), with their powerful generative capabilities and vast knowledge, empower various tasks in everyday life. However, these abilities are primarily concentrated in high-resource languages, leaving low-resource languages with
Externí odkaz:
http://arxiv.org/abs/2411.16300
With the development of artificial intelligence, more and more attention has been put onto generative models, which represent the creativity, a very important aspect of intelligence. In recent years, diffusion models have been studied and proven to b
Externí odkaz:
http://arxiv.org/abs/2411.15199
Reliable motion forecasting of surrounding agents is essential for ensuring the safe operation of autonomous vehicles. Many existing trajectory prediction methods rely heavily on high-definition (HD) maps as strong driving priors. However, the availa
Externí odkaz:
http://arxiv.org/abs/2411.10961
Autor:
Chen, Runteng, Zhang, Jun, Wang, Zelong, Lu, Ke, Peng, Yi, Zhao, Jianfa, Liu, Xiaodong, Feng, Shaomin, Liu, Ruibin, Xiao, Chuan, Jin, Changqing
Publikováno v:
Science Bulletin, 69(24):3812 (2024)
In this work, the long-sought cg-N with N-N single bond has been synthesized for the first time by a thermal-driven-only chemical route at ambient conditions. The successful synthesis of cg-N was achieved by first creating a solution of azides, which
Externí odkaz:
http://arxiv.org/abs/2411.10331
Autor:
Muhtar, Dilxat, Shen, Yelong, Yang, Yaming, Liu, Xiaodong, Lu, Yadong, Liu, Jianfeng, Zhan, Yuefeng, Sun, Hao, Deng, Weiwei, Sun, Feng, Zhang, Xueliang, Gao, Jianfeng, Chen, Weizhu, Zhang, Qi
In-context learning (ICL) allows large language models (LLMs) to adapt to new tasks directly from the given demonstrations without requiring gradient updates. While recent advances have expanded context windows to accommodate more demonstrations, thi
Externí odkaz:
http://arxiv.org/abs/2411.09289
Autor:
Li, Xiaopeng, Wang, Shangwen, Li, Shasha, Ma, Jun, Yu, Jie, Liu, Xiaodong, Wang, Jing, Ji, Bin, Zhang, Weimin
Large Language Models for Code (LLMs4Code) have been found to exhibit outstanding performance in the software engineering domain, especially the remarkable performance in coding tasks. However, even the most advanced LLMs4Code can inevitably contain
Externí odkaz:
http://arxiv.org/abs/2411.06638
Autor:
Chen, Tong, Fang, Hao, Xia, Patrick, Liu, Xiaodong, Van Durme, Benjamin, Zettlemoyer, Luke, Gao, Jianfeng, Cheng, Hao
Large language models (LMs) are typically adapted to improve performance on new contexts (\eg text prompts that define new tasks or domains) through fine-tuning or prompting. However, there is an accuracy compute tradeoff -- fine-tuning incurs signif
Externí odkaz:
http://arxiv.org/abs/2411.05877
Autor:
Sun, Chung-En, Liu, Xiaodong, Yang, Weiwei, Weng, Tsui-Wei, Cheng, Hao, San, Aidan, Galley, Michel, Gao, Jianfeng
Recent research has shown that Large Language Models (LLMs) are vulnerable to automated jailbreak attacks, where adversarial suffixes crafted by algorithms appended to harmful queries bypass safety alignment and trigger unintended responses. Current
Externí odkaz:
http://arxiv.org/abs/2410.18469