Zobrazeno 1 - 10
of 26 423
pro vyhledávání: '"Zhou,Xin"'
Autor:
Zhang, Beiqi, Liang, Peng, Zhou, Xin, Zhou, Xiyu, Lo, David, Feng, Qiong, Li, Zengyang, Li, Lin
Code smells are suboptimal coding practices that negatively impact the quality of software systems. Existing detection methods, relying on heuristics or Machine Learning (ML) and Deep Learning (DL) techniques, often face limitations such as unsatisfa
Externí odkaz:
http://arxiv.org/abs/2412.13801
Autor:
Sun, Yan, Yang, Ji, Zhang, Shaobo, Yan, Qing-Zeng, Su, Yang, Chen, Xuepeng, Zhou, Xin, Xu, Ye, Wang, Hongchi, Wang, Min, Jiang, Zhibo, Sun, Ji-Xian, Lu, Deng-Rong, Ju, Bing-Gang, Zhang, Xu-Guo
Based on 32162 molecular clouds from the Milky Way Imaging Scroll Painting project, we obtain new face-on molecular gas maps of the northern outer Galaxy. The total molecular gas surface density map reveals three segments of spirals, extending 16-43
Externí odkaz:
http://arxiv.org/abs/2411.11220
Autor:
Zhou, Xin, Zhang, Lei, Zhang, Honglei, Zhang, Yixin, Zhang, Xiaoxiong, Zhang, Jie, Shen, Zhiqi
Human behavioral patterns and consumption paradigms have emerged as pivotal determinants in environmental degradation and climate change, with quotidian decisions pertaining to transportation, energy utilization, and resource consumption collectively
Externí odkaz:
http://arxiv.org/abs/2411.07658
Autor:
Yang, Guang, Zhou, Yu, Cheng, Wei, Zhang, Xiangyu, Chen, Xiang, Zhuo, Terry Yue, Liu, Ke, Zhou, Xin, Lo, David, Chen, Taolue
The widespread use of Large Language Models (LLMs) in software engineering has intensified the need for improved model and resource efficiency. In particular, for neural code generation, LLMs are used to translate function/method signature and DocStr
Externí odkaz:
http://arxiv.org/abs/2410.22793
Autor:
Zhou, Xin, Nie, Ping, Guo, Yiwen, Wei, Haojie, Zhang, Zhanqiu, Minervini, Pasquale, Ma, Ruotian, Gui, Tao, Zhang, Qi, Huang, Xuanjing
Retrieval-Augmented Generation (RAG) significantly improved the ability of Large Language Models (LLMs) to solve knowledge-intensive tasks. While existing research seeks to enhance RAG performance by retrieving higher-quality documents or designing R
Externí odkaz:
http://arxiv.org/abs/2410.15438
Recently, leveraging pre-training techniques to enhance point cloud models has become a hot research topic. However, existing approaches typically require full fine-tuning of pre-trained models to achieve satisfied performance on downstream tasks, ac
Externí odkaz:
http://arxiv.org/abs/2410.08114
Autor:
Qu, Shilin, Wang, Weiqing, Zhou, Xin, Zhan, Haolan, Li, Zhuang, Qu, Lizhen, Luo, Linhao, Li, Yuan-Fang, Haffari, Gholamreza
Publikováno v:
TOMM 2024
Sociocultural norms serve as guiding principles for personal conduct in social interactions, emphasizing respect, cooperation, and appropriate behavior, which is able to benefit tasks including conversational information retrieval, contextual informa
Externí odkaz:
http://arxiv.org/abs/2410.03049
Autor:
Xu, Gang, Zhou, Xin, Wang, Molin, Zhang, Boya, Jiang, Wenhao, Laden, Francine, Suh, Helen H., Szpiro, Adam A., Spiegelman, Donna, Wang, Zuoheng
One way to quantify exposure to air pollution and its constituents in epidemiologic studies is to use an individual's nearest monitor. This strategy results in potential inaccuracy in the actual personal exposure, introducing bias in estimating the h
Externí odkaz:
http://arxiv.org/abs/2410.07135
Autor:
Cioppa, Anthony, Giancola, Silvio, Somers, Vladimir, Joos, Victor, Magera, Floriane, Held, Jan, Ghasemzadeh, Seyed Abolfazl, Zhou, Xin, Seweryn, Karolina, Kowalczyk, Mateusz, Mróz, Zuzanna, Łukasik, Szymon, Hałoń, Michał, Mkhallati, Hassan, Deliège, Adrien, Hinojosa, Carlos, Sanchez, Karen, Mansourian, Amir M., Miralles, Pierre, Barnich, Olivier, De Vleeschouwer, Christophe, Alahi, Alexandre, Ghanem, Bernard, Van Droogenbroeck, Marc, Gorski, Adam, Clapés, Albert, Boiarov, Andrei, Afanasiev, Anton, Xarles, Artur, Scott, Atom, Lim, ByoungKwon, Yeung, Calvin, Gonzalez, Cristian, Rüfenacht, Dominic, Pacilio, Enzo, Deuser, Fabian, Altawijri, Faisal Sami, Cachón, Francisco, Kim, HanKyul, Wang, Haobo, Choe, Hyeonmin, Kim, Hyunwoo J, Kim, Il-Min, Kang, Jae-Mo, Tursunboev, Jamshid, Yang, Jian, Hong, Jihwan, Lee, Jimin, Zhang, Jing, Lee, Junseok, Zhang, Kexin, Habel, Konrad, Jiao, Licheng, Li, Linyi, Gutiérrez-Pérez, Marc, Ortega, Marcelo, Li, Menglong, Lopatto, Milosz, Kasatkin, Nikita, Nemtsev, Nikolay, Oswald, Norbert, Udin, Oleg, Kononov, Pavel, Geng, Pei, Alotaibi, Saad Ghazai, Kim, Sehyung, Ulasen, Sergei, Escalera, Sergio, Zhang, Shanshan, Yang, Shuyuan, Moon, Sunghwan, Moeslund, Thomas B., Shandyba, Vasyl, Golovkin, Vladimir, Dai, Wei, Chung, WonTaek, Liu, Xinyu, Zhu, Yongqiang, Kim, Youngseo, Li, Yuan, Yang, Yuting, Xiao, Yuxuan, Cheng, Zehua, Li, Zhihao
The SoccerNet 2024 challenges represent the fourth annual video understanding challenges organized by the SoccerNet team. These challenges aim to advance research across multiple themes in football, including broadcast video understanding, field unde
Externí odkaz:
http://arxiv.org/abs/2409.10587
Autor:
Zhou, Xin, Peng, Xiaojing
EEG-based emotion recognition holds significant potential in the field of brain-computer interfaces. A key challenge lies in extracting discriminative spatiotemporal features from electroencephalogram (EEG) signals. Existing studies often rely on dom
Externí odkaz:
http://arxiv.org/abs/2409.07589