Zobrazeno 1 - 10
of 80
pro vyhledávání: '"Liu, Shukai"'
Autor:
Chai, Linzheng, Liu, Shukai, Yang, Jian, Yin, Yuwei, Jin, Ke, Liu, Jiaheng, Sun, Tao, Zhang, Ge, Ren, Changyu, Guo, Hongcheng, Wang, Zekun, Wang, Boyang, Wu, Xianjie, Wang, Bing, Li, Tongliang, Yang, Liqun, Duan, Sufeng, Li, Zhoujun
Code large language models (LLMs) have shown remarkable advances in code understanding, completion, and generation tasks. Programming benchmarks, comprised of a selection of code challenges and corresponding test cases, serve as a standard to evaluat
Externí odkaz:
http://arxiv.org/abs/2406.07436
Autor:
Zhu, Yinghao, Ren, Changyu, Xie, Shiyun, Liu, Shukai, Ji, Hangyuan, Wang, Zixiang, Sun, Tao, He, Long, Li, Zhoujun, Zhu, Xi, Pan, Chengwei
The integration of multimodal Electronic Health Records (EHR) data has significantly improved clinical predictive capabilities. Leveraging clinical notes and multivariate time-series EHR, existing models often lack the medical context relevent to cli
Externí odkaz:
http://arxiv.org/abs/2402.07016
Interactive reinforcement learning has shown promise in learning complex robotic tasks. However, the process can be human-intensive due to the requirement of a large amount of interactive feedback. This paper presents a new method that uses scores pr
Externí odkaz:
http://arxiv.org/abs/2307.05405
Publikováno v:
KDD-2022
Cross-domain recommendation (CDR) aims to provide better recommendation results in the target domain with the help of the source domain, which is widely used and explored in real-world systems. However, CDR in the matching (i.e., candidate generation
Externí odkaz:
http://arxiv.org/abs/2112.00999
Publikováno v:
In Journal of Environmental Chemical Engineering April 2024 12(2)
Publikováno v:
IEEE Transactions on Big Data, 2021
Recently, real-world recommendation systems need to deal with millions of candidates. It is extremely challenging to conduct sophisticated end-to-end algorithms on the entire corpus due to the tremendous computation costs. Therefore, conventional rec
Externí odkaz:
http://arxiv.org/abs/2102.03787
Autor:
Liu, Shukai1 (AUTHOR) 2131505@tongji.edu.cn, Yin, Changqing1 (AUTHOR) yinchangqing@tongji.edu.cn, Zhang, Huijuan1 (AUTHOR)
Publikováno v:
Sensors (14248220). Feb2024, Vol. 24 Issue 4, p1187. 20p.
Session-based target behavior prediction aims to predict the next item to be interacted with specific behavior types (e.g., clicking). Although existing methods for session-based behavior prediction leverage powerful representation learning approache
Externí odkaz:
http://arxiv.org/abs/2002.07993
Autor:
Liu, Shukai, Cui, Zhengguo, Ding, Dongsheng, Bai, Ying, Chen, Jianlei, Cui, Hongwu, Su, Rongguo, Qu, Keming
Publikováno v:
In Journal of Environmental Management 15 December 2023 348
Autor:
Zhou, Hongxi, Liu, Shukai, Yang, Ming, Liu, Xianchao, Zhang, Xingchao, Zhou, Xin, Han, Jiayue, Gou, Jun, Wang, Jun, Jiang, Yadong
Publikováno v:
In Acta Materialia March 2022 226