Zobrazeno 1 - 10
of 476
pro vyhledávání: '"Zheni A"'
Autor:
Zeng, Zheni, Chen, Yuxuan, Yu, Shi, Wang, Ruobing, Yan, Yukun, Liu, Zhenghao, Wang, Shuo, Han, Xu, Liu, Zhiyuan, Sun, Maosong
Humans can utilize techniques to quickly acquire knowledge from specific materials in advance, such as creating self-assessment questions, enabling us to achieving related tasks more efficiently. In contrast, large language models (LLMs) usually reli
Externí odkaz:
http://arxiv.org/abs/2411.14790
Autor:
Li, Xinze, Mei, Sen, Liu, Zhenghao, Yan, Yukun, Wang, Shuo, Yu, Shi, Zeng, Zheni, Chen, Hao, Yu, Ge, Liu, Zhiyuan, Sun, Maosong, Xiong, Chenyan
Retrieval-Augmented Generation (RAG) has proven its effectiveness in mitigating hallucinations in Large Language Models (LLMs) by retrieving knowledge from external resources. To adapt LLMs for RAG pipelines, current approaches use instruction tuning
Externí odkaz:
http://arxiv.org/abs/2410.13509
Autor:
Zeng, Zheni, Chen, Jiayi, Chen, Huimin, Yan, Yukun, Chen, Yuxuan, Liu, Zhenghao, Liu, Zhiyuan, Sun, Maosong
Large language models exhibit aspects of human-level intelligence that catalyze their application as human-like agents in domains such as social simulations, human-machine interactions, and collaborative multi-agent systems. However, the absence of d
Externí odkaz:
http://arxiv.org/abs/2407.12393
Autor:
Xu, Zhipeng, Liu, Zhenghao, Yan, Yukun, Wang, Shuo, Yu, Shi, Zeng, Zheni, Xiao, Chaojun, Liu, Zhiyuan, Yu, Ge, Xiong, Chenyan
Retrieval-Augmented Generation (RAG) enables Large Language Models (LLMs) to leverage external knowledge, enhancing their performance on knowledge-intensive tasks. However, existing RAG models often treat LLMs as passive recipients of information, wh
Externí odkaz:
http://arxiv.org/abs/2402.13547
Autor:
Song, Chenyang, Han, Xu, Zeng, Zheni, Li, Kuai, Chen, Chen, Liu, Zhiyuan, Sun, Maosong, Yang, Tao
Continual learning necessitates the continual adaptation of models to newly emerging tasks while minimizing the catastrophic forgetting of old ones. This is extremely challenging for large language models (LLMs) with vanilla full-parameter tuning due
Externí odkaz:
http://arxiv.org/abs/2309.14763
Autor:
Zeng, Zheni, Yin, Bangchen, Wang, Shipeng, Liu, Jiarui, Yang, Cheng, Yao, Haishen, Sun, Xingzhi, Sun, Maosong, Xie, Guotong, Liu, Zhiyuan
Natural language is expected to be a key medium for various human-machine interactions in the era of large language models. When it comes to the biochemistry field, a series of tasks around molecules (e.g., property prediction, molecule mining, etc.)
Externí odkaz:
http://arxiv.org/abs/2306.11976
Autor:
Qin, Yujia, Hu, Shengding, Lin, Yankai, Chen, Weize, Ding, Ning, Cui, Ganqu, Zeng, Zheni, Huang, Yufei, Xiao, Chaojun, Han, Chi, Fung, Yi Ren, Su, Yusheng, Wang, Huadong, Qian, Cheng, Tian, Runchu, Zhu, Kunlun, Liang, Shihao, Shen, Xingyu, Xu, Bokai, Zhang, Zhen, Ye, Yining, Li, Bowen, Tang, Ziwei, Yi, Jing, Zhu, Yuzhang, Dai, Zhenning, Yan, Lan, Cong, Xin, Lu, Yaxi, Zhao, Weilin, Huang, Yuxiang, Yan, Junxi, Han, Xu, Sun, Xian, Li, Dahai, Phang, Jason, Yang, Cheng, Wu, Tongshuang, Ji, Heng, Liu, Zhiyuan, Sun, Maosong
Humans possess an extraordinary ability to create and utilize tools, allowing them to overcome physical limitations and explore new frontiers. With the advent of foundation models, AI systems have the potential to be equally adept in tool use as huma
Externí odkaz:
http://arxiv.org/abs/2304.08354
Autor:
Wang, Zheni1 (AUTHOR) steveecarroll82@gmail.com, Carroll, Steve1 (AUTHOR), Wang, Eric H.2 (AUTHOR) eriwang@ucdavis.edu
Publikováno v:
Behavioral Sciences (2076-328X). Nov2024, Vol. 14 Issue 11, p1014. 11p.
Publikováno v:
Synthetic and Systems Biotechnology, Vol 9, Iss 2, Pp 259-268 (2024)
Descriptors play a pivotal role in enzyme design for the greener synthesis of biochemicals, as they could characterize enzymes and chemicals from the physicochemical and evolutionary perspective. This study examined the effects of various descriptors
Externí odkaz:
https://doaj.org/article/c57f1e54e27d43e2885d10d01c21e8ab
Autor:
Tang, Dongfang a, b, Xu, Jiahui c, Bao, Wenhu a, Xu, Fanping a, Qi, Jieqiong a, Tan, Zheni a, Li, Chuanli a, Luo, Xiaofang a, You, Xia b, Rong, Mingqiang b, ∗∗, Liu, Zhonghua b, ∗∗∗, Tang, Cheng b, ⁎
Publikováno v:
In European Journal of Pharmacology 5 February 2025 988