Zobrazeno 1 - 10
of 2 266
pro vyhledávání: '"Zhang Chenyang"'
Autor:
MAO Kebiao, ZHANG Chenyang, SHI Jiancheng, WANG Xuming, GUO Zhonghua, LI Chunshu, DONG Lixin, WU Menxin, SUN Ruijing, WU Shengli, JI Dabin, JIANG Lingmei, ZHAO Tianjie, QIU Yubao, DU Yongming, XU Tongren
Publikováno v:
智慧农业, Vol 5, Iss 2, Pp 161-171 (2023)
目的/意义人工智能（Artificial Intelligence，AI）技术已在学术和工程应用领域掀起了研究高潮，在地球物理参数和农业气象遥感参数反演方面也表现出了强大的应用潜力。目前大部分AI技术在地
Externí odkaz:
https://doaj.org/article/a5b1270120b14d769c04b66066955160
An $r$-graph is called $t$-cancellative if for arbitrary $t+2$ distinct edges $A_1,\ldots,A_t,B,C$, it holds that $(\cup_{i=1}^t A_i)\cup B\neq (\cup_{i=1}^t A_i)\cup C$; it is called $t$-union-free if for arbitrary two distinct subsets $\mathcal{A},
Externí odkaz:
http://arxiv.org/abs/2411.07908
Autor:
Kahatapitiya, Kumara, Liu, Haozhe, He, Sen, Liu, Ding, Jia, Menglin, Zhang, Chenyang, Ryoo, Michael S., Xie, Tian
Generating temporally-consistent high-fidelity videos can be computationally expensive, especially over longer temporal spans. More-recent Diffusion Transformers (DiTs) -- despite making significant headway in this context -- have only heightened suc
Externí odkaz:
http://arxiv.org/abs/2411.02397
Different from the traditional semi-supervised learning paradigm that is constrained by the close-world assumption, Generalized Category Discovery (GCD) presumes that the unlabeled dataset contains new categories not appearing in the labeled set, and
Externí odkaz:
http://arxiv.org/abs/2410.21705
Autor:
Lin, Jiayi, Zhang, Chenyang, Tong, Haibo, Zhang, Dongyu, Hong, Qingqing, Hou, Bingxuan, Wang, Junli
Multi-Span Question Answering (MSQA) requires models to extract one or multiple answer spans from a given context to answer a question. Prior work mainly focuses on designing specific methods or applying heuristic strategies to encourage models to pr
Externí odkaz:
http://arxiv.org/abs/2410.16788
Autor:
Zhang, Chenyang, Lin, Jiayi, Tong, Haibo, Hou, Bingxuan, Zhang, Dongyu, Li, Jialin, Wang, Junli
Large language models (LLMs) show remarkable abilities with instruction tuning. However, they fail to achieve ideal tasks when lacking high-quality instruction tuning data on target tasks. Multi-Aspect Controllable Text Generation (MCTG) is a represe
Externí odkaz:
http://arxiv.org/abs/2410.14144
Large language models (LLMs) have shown various ability on natural language processing, including problems about causality. It is not intuitive for LLMs to command causality, since pretrained models usually work on statistical associations, and do no
Externí odkaz:
http://arxiv.org/abs/2408.14380
Autor:
Ouyang, Yang, Zhang, Chenyang, Wang, He, Ma, Tianle, Jiang, Chang, Yan, Yuheng, Yan, Zuoqin, Ma, Xiaojuan, Shi, Chuhan, Li, Quan
In healthcare, AI techniques are widely used for tasks like risk assessment and anomaly detection. Despite AI's potential as a valuable assistant, its role in complex medical data analysis often oversimplifies human-AI collaboration dynamics. To addr
Externí odkaz:
http://arxiv.org/abs/2407.14769
Adam has become one of the most favored optimizers in deep learning problems. Despite its success in practice, numerous mysteries persist regarding its theoretical understanding. In this paper, we study the implicit bias of Adam in linear logistic re
Externí odkaz:
http://arxiv.org/abs/2406.10650
PowerShell is a powerful and versatile task automation tool. Unfortunately, it is also widely abused by cyber attackers. To bypass malware detection and hinder threat analysis, attackers often employ diverse techniques to obfuscate malicious PowerShe
Externí odkaz:
http://arxiv.org/abs/2406.04027