Zobrazeno 1 - 10
of 60 719
pro vyhledávání: '"Lin CHen"'
Autor:
Vogt B; Department of Urology, Polyclinique de Blois, 1 rue Robert Debré, 41260, La Chaussée Saint-Victor, France. message@benoitvogt.fr.
Publikováno v:
World journal of urology [World J Urol] 2024 May 15; Vol. 42 (1), pp. 327. Date of Electronic Publication: 2024 May 15.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Zheng, Yihang, Li, Bo, Lin, Zhenghao, Luo, Yi, Zhou, Xuanhe, Lin, Chen, Su, Jinsong, Li, Guoliang, Li, Shifu
The development of Large Language Models (LLMs) has revolutionized Q&A across various industries, including the database domain. However, there is still a lack of a comprehensive benchmark to evaluate the capabilities of different LLMs and their modu
Externí odkaz:
http://arxiv.org/abs/2409.04475
Autor:
Lin, Chen, Bruinsma, Robijn
Active liquid-liquid phase separation (LLPS) in a confining environment is believed to play an important role in cell biology. Recently, it was shown that when active noise at the microscopic level is included in the classical theory of nucleation an
Externí odkaz:
http://arxiv.org/abs/2408.07876
Autor:
Xv, Guipeng, Li, Xinyu, Xie, Ruobing, Lin, Chen, Liu, Chong, Xia, Feng, Kang, Zhanhui, Lin, Leyu
Multi-modal recommender systems (MRSs) are pivotal in diverse online web platforms and have garnered considerable attention in recent years. However, previous studies overlook the challenges of (1) noisy multi-modal content, (2) noisy user feedback,
Externí odkaz:
http://arxiv.org/abs/2406.12501
Autor:
McConwell, Alison K.
Publikováno v:
History and Philosophy of the Life Sciences, 2020 Mar 01. 42(1), 1-4.
Externí odkaz:
https://www.jstor.org/stable/45410580
Autor:
Wei, Gengchen, Pang, Xinle, Zhang, Tianning, Sun, Yu, Qian, Xun, Lin, Chen, Zhong, Han-Sen, Ouyang, Wanli
With over 200 million published academic documents and millions of new documents being written each year, academic researchers face the challenge of searching for information within this vast corpus. However, existing retrieval systems struggle to un
Externí odkaz:
http://arxiv.org/abs/2405.11461
Autor:
Gao, Peng, Zhuo, Le, Liu, Dongyang, Du, Ruoyi, Luo, Xu, Qiu, Longtian, Zhang, Yuhang, Lin, Chen, Huang, Rongjie, Geng, Shijie, Zhang, Renrui, Xi, Junlin, Shao, Wenqi, Jiang, Zhengkai, Yang, Tianshuo, Ye, Weicai, Tong, He, He, Jingwen, Qiao, Yu, Li, Hongsheng
Sora unveils the potential of scaling Diffusion Transformer for generating photorealistic images and videos at arbitrary resolutions, aspect ratios, and durations, yet it still lacks sufficient implementation details. In this technical report, we int
Externí odkaz:
http://arxiv.org/abs/2405.05945
Autor:
Lin, Zhenghao, Gou, Zhibin, Gong, Yeyun, Liu, Xiao, Shen, Yelong, Xu, Ruochen, Lin, Chen, Yang, Yujiu, Jiao, Jian, Duan, Nan, Chen, Weizhu
Previous language model pre-training methods have uniformly applied a next-token prediction loss to all training tokens. Challenging this norm, we posit that ''Not all tokens in a corpus are equally important for language model training''. Our initia
Externí odkaz:
http://arxiv.org/abs/2404.07965