Zobrazeno 1 - 10
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pro vyhledávání: '"Li, Mingming"'
Autor:
Kuai, Zhirui, Chen, Zuxu, Wang, Huimu, Li, Mingming, Miao, Dadong, Wang, Binbin, Chen, Xusong, Kuang, Li, Han, Yuxing, Wang, Jiaxing, Tang, Guoyu, Liu, Lin, Wang, Songlin, Zhuo, Jingwei
Generative retrieval (GR) has emerged as a transformative paradigm in search and recommender systems, leveraging numeric-based identifier representations to enhance efficiency and generalization. Notably, methods like TIGER employing Residual Quantiz
Externí odkaz:
http://arxiv.org/abs/2407.21488
Autor:
Li, Mingming, Wang, Huimu, Chen, Zuxu, Nie, Guangtao, Qiu, Yiming, Wang, Binbin, Tang, Guoyu, Liu, Lin, Zhuo, Jingwei
Generative retrieval introduces a groundbreaking paradigm to document retrieval by directly generating the identifier of a pertinent document in response to a specific query. This paradigm has demonstrated considerable benefits and potential, particu
Externí odkaz:
http://arxiv.org/abs/2407.19829
Recently, relational metric learning methods have been received great attention in recommendation community, which is inspired by the translation mechanism in knowledge graph. Different from the knowledge graph where the entity-to-entity relations ar
Externí odkaz:
http://arxiv.org/abs/2406.10246
Autor:
Wang, Huimu, Li, Mingming, Miao, Dadong, Wang, Songlin, Tang, Guoyu, Liu, Lin, Xu, Sulong, Hu, Jinghe
Re-ranking is a process of rearranging ranking list to more effectively meet user demands by accounting for the interrelationships between items. Existing methods predominantly enhance the precision of search results, often at the expense of diversit
Externí odkaz:
http://arxiv.org/abs/2405.15521
Autor:
Xu, Enqiang, Qiu, Yiming, Bai, Junyang, Zhang, Ping, Miao, Dadong, Wang, Songlin, Tang, Guoyu, Liu, Lin, Li, Mingming
In large e-commerce platforms, search systems are typically composed of a series of modules, including recall, pre-ranking, and ranking phases. The pre-ranking phase, serving as a lightweight module, is crucial for filtering out the bulk of products
Externí odkaz:
http://arxiv.org/abs/2405.05606
Autor:
DeepSeek-AI, Liu, Aixin, Feng, Bei, Wang, Bin, Wang, Bingxuan, Liu, Bo, Zhao, Chenggang, Dengr, Chengqi, Ruan, Chong, Dai, Damai, Guo, Daya, Yang, Dejian, Chen, Deli, Ji, Dongjie, Li, Erhang, Lin, Fangyun, Luo, Fuli, Hao, Guangbo, Chen, Guanting, Li, Guowei, Zhang, H., Xu, Hanwei, Yang, Hao, Zhang, Haowei, Ding, Honghui, Xin, Huajian, Gao, Huazuo, Li, Hui, Qu, Hui, Cai, J. L., Liang, Jian, Guo, Jianzhong, Ni, Jiaqi, Li, Jiashi, Chen, Jin, Yuan, Jingyang, Qiu, Junjie, Song, Junxiao, Dong, Kai, Gao, Kaige, Guan, Kang, Wang, Lean, Zhang, Lecong, Xu, Lei, Xia, Leyi, Zhao, Liang, Zhang, Liyue, Li, Meng, Wang, Miaojun, Zhang, Mingchuan, Zhang, Minghua, Tang, Minghui, Li, Mingming, Tian, Ning, Huang, Panpan, Wang, Peiyi, Zhang, Peng, Zhu, Qihao, Chen, Qinyu, Du, Qiushi, Chen, R. J., Jin, R. L., Ge, Ruiqi, Pan, Ruizhe, Xu, Runxin, 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, Zheng, Size, Wang, T., Pei, Tian, Yuan, Tian, Sun, Tianyu, Xiao, W. L., Zeng, Wangding, An, Wei, Liu, Wen, Liang, Wenfeng, Gao, Wenjun, Zhang, Wentao, Li, X. Q., Jin, Xiangyue, Wang, Xianzu, Bi, Xiao, Liu, Xiaodong, Wang, Xiaohan, Shen, Xiaojin, Chen, Xiaokang, Chen, Xiaosha, Nie, Xiaotao, Sun, Xiaowen, Wang, Xiaoxiang, Liu, Xin, Xie, Xin, Yu, Xingkai, Song, Xinnan, Zhou, Xinyi, Yang, Xinyu, Lu, Xuan, Su, Xuecheng, Wu, Y., Li, Y. K., Wei, Y. X., Zhu, Y. X., Xu, Yanhong, Huang, Yanping, Li, Yao, Zhao, Yao, Sun, Yaofeng, Li, Yaohui, Wang, Yaohui, Zheng, Yi, Zhang, Yichao, Xiong, Yiliang, Zhao, Yilong, He, Ying, Tang, Ying, Piao, Yishi, Dong, Yixin, Tan, Yixuan, Liu, Yiyuan, Wang, Yongji, Guo, Yongqiang, Zhu, Yuchen, Wang, Yuduan, Zou, Yuheng, Zha, Yukun, Ma, Yunxian, Yan, Yuting, You, Yuxiang, Liu, Yuxuan, Ren, Z. Z., Ren, Zehui, Sha, Zhangli, Fu, Zhe, Huang, Zhen, Zhang, Zhen, Xie, Zhenda, Hao, Zhewen, Shao, Zhihong, Wen, Zhiniu, Xu, Zhipeng, Zhang, Zhongyu, Li, Zhuoshu, Wang, Zihan, Gu, Zihui, Li, Zilin, Xie, Ziwei
We present DeepSeek-V2, a strong Mixture-of-Experts (MoE) language model characterized by economical training and efficient inference. It comprises 236B total parameters, of which 21B are activated for each token, and supports a context length of 128
Externí odkaz:
http://arxiv.org/abs/2405.04434
Autor:
Lin, Yuqi, Chen, Minghao, Zhang, Kaipeng, Li, Hengjia, Li, Mingming, Yang, Zheng, Lv, Dongqin, Lin, Binbin, Liu, Haifeng, Cai, Deng
Contrastive Language-Image Pre-training (CLIP) has demonstrated impressive capabilities in open-vocabulary classification. The class token in the image encoder is trained to capture the global features to distinguish different text descriptions super
Externí odkaz:
http://arxiv.org/abs/2312.12828
Query intent classification, which aims at assisting customers to find desired products, has become an essential component of the e-commerce search. Existing query intent classification models either design more exquisite models to enhance the repres
Externí odkaz:
http://arxiv.org/abs/2303.15870
Autor:
Wang, Binbin, Li, Mingming, Zeng, Zhixiong, Zhuo, Jingwei, Wang, Songlin, Xu, Sulong, Long, Bo, Yan, Weipeng
Retrieving relevant items that match users' queries from billion-scale corpus forms the core of industrial e-commerce search systems, in which embedding-based retrieval (EBR) methods are prevailing. These methods adopt a two-tower framework to learn
Externí odkaz:
http://arxiv.org/abs/2303.11009
Autor:
Wang, Qian1,2, Li, Mingming1,2 wqharbour@outlook.com, Guo, Pingping1,2, Gao, Liang1,2, Weng, Ling1,2, Huang, Wenmei1,2
Publikováno v:
Scientific Reports. 9/6/2024, Vol. 14 Issue 1, p1-12. 12p.