Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Zeng, Zheni"'
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:
Yuan, Sha, Zhao, Hanyu, Zhao, Shuai, Leng, Jiahong, Liang, Yangxiao, Wang, Xiaozhi, Yu, Jifan, Lv, Xin, Shao, Zhou, He, Jiaao, Lin, Yankai, Han, Xu, Liu, Zhenghao, Ding, Ning, Rao, Yongming, Gao, Yizhao, Zhang, Liang, Ding, Ming, Fang, Cong, Wang, Yisen, Long, Mingsheng, Zhang, Jing, Dong, Yinpeng, Pang, Tianyu, Cui, Peng, Huang, Lingxiao, Liang, Zheng, Shen, Huawei, Zhang, Hui, Zhang, Quanshi, Dong, Qingxiu, Tan, Zhixing, Wang, Mingxuan, Wang, Shuo, Zhou, Long, Li, Haoran, Bao, Junwei, Pan, Yingwei, Zhang, Weinan, Yu, Zhou, Yan, Rui, Shi, Chence, Xu, Minghao, Zhang, Zuobai, Wang, Guoqiang, Pan, Xiang, Li, Mengjie, Chu, Xiaoyu, Yao, Zijun, Zhu, Fangwei, Cao, Shulin, Xue, Weicheng, Ma, Zixuan, Zhang, Zhengyan, Hu, Shengding, Qin, Yujia, Xiao, Chaojun, Zeng, Zheni, Cui, Ganqu, Chen, Weize, Zhao, Weilin, Yao, Yuan, Li, Peng, Zheng, Wenzhao, Zhao, Wenliang, Wang, Ziyi, Zhang, Borui, Fei, Nanyi, Hu, Anwen, Ling, Zenan, Li, Haoyang, Cao, Boxi, Han, Xianpei, Zhan, Weidong, Chang, Baobao, Sun, Hao, Deng, Jiawen, Zheng, Chujie, Li, Juanzi, Hou, Lei, Cao, Xigang, Zhai, Jidong, Liu, Zhiyuan, Sun, Maosong, Lu, Jiwen, Lu, Zhiwu, Jin, Qin, Song, Ruihua, Wen, Ji-Rong, Lin, Zhouchen, Wang, Liwei, Su, Hang, Zhu, Jun, Sui, Zhifang, Zhang, Jiajun, Liu, Yang, He, Xiaodong, Huang, Minlie, Tang, Jian, Tang, Jie
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm. Researchers have achieved various outcomes in the construction of BMs and the BM application in many fields. At present,
Externí odkaz:
http://arxiv.org/abs/2203.14101
Autor:
Yao, Yuan, Dong, Qingxiu, Guan, Jian, Cao, Boxi, Zhang, Zhengyan, Xiao, Chaojun, Wang, Xiaozhi, Qi, Fanchao, Bao, Junwei, Nie, Jinran, Zeng, Zheni, Gu, Yuxian, Zhou, Kun, Huang, Xuancheng, Li, Wenhao, Ren, Shuhuai, Lu, Jinliang, Xu, Chengqiang, Wang, Huadong, Zeng, Guoyang, Zhou, Zile, Zhang, Jiajun, Li, Juanzi, Huang, Minlie, Yan, Rui, He, Xiaodong, Wan, Xiaojun, Zhao, Xin, Sun, Xu, Liu, Yang, Liu, Zhiyuan, Han, Xianpei, Yang, Erhong, Sui, Zhifang, Sun, Maosong
Realizing general-purpose language intelligence has been a longstanding goal for natural language processing, where standard evaluation benchmarks play a fundamental and guiding role. We argue that for general-purpose language intelligence evaluation
Externí odkaz:
http://arxiv.org/abs/2112.13610
Publikováno v:
In Synthetic and Systems Biotechnology June 2024 9(2):259-268
Autor:
Li, Mengdi, Weber, Cornelius, Kerzel, Matthias, Lee, Jae Hee, Zeng, Zheni, Liu, Zhiyuan, Wermter, Stefan
Reasoning about potential occlusions is essential for robots to efficiently predict whether an object exists in an environment. Though existing work shows that a robot with active perception can achieve various tasks, it is still unclear if occlusion
Externí odkaz:
http://arxiv.org/abs/2107.12095