Zobrazeno 1 - 10
of 4 546
pro vyhledávání: '"Shi Ling"'
Autor:
Shi Ling
Publikováno v:
SHS Web of Conferences, Vol 181, p 04023 (2024)
With the rapid development of the digital economy, the demand for language talents has increased significantly, especially for Business English majors. However, the traditional talent cultivation model has failed to keep up with the needs of regional
Externí odkaz:
https://doaj.org/article/38ccc0f1eca3487889675257881050d9
Autor:
Shi Ling, Jin Xuexin, Li Zheng, Gong Rui, Guo Yang, Ma Jiudong, Zhang Yang, Cai Benzhi, Yang Baofeng, Gong Dongmei, Pan Zhenwei
Publikováno v:
Acta Biochimica et Biophysica Sinica, Vol 54, Pp 199-208 (2022)
Methyltransferase-like 3 (Mettl3) is a component of methyltransferase complex that mediates m6A modification of RNAs, and participates in multiple biological processes. However, the role of Mettl3 in cardiac electrophysiology remains unknown. This st
Externí odkaz:
https://doaj.org/article/b05c54c16bac446082dd6f46efc601dc
Autor:
Ruth Jinfen Chai, Hendrikje Werner, Peter Yiqing Li, Yin Loon Lee, Khaing Thet Nyein, Irina Solovei, Tuan Danh Anh Luu, Bhavya Sharma, Raju Navasankari, Martina Maric, Lois Yu En Sim, Ying Jie Loh, Edita Aliwarga, Jason Wen Long Cheong, Alexandre Chojnowski, Matias Ilmari Autio, Yu Haiyang, Kenneth Kian Boon Tan, Choong Tat Keng, Shi Ling Ng, Wei Leong Chew, Michael Ferenczi, Brian Burke, Roger Sik Yin Foo, Colin L. Stewart
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-16 (2021)
Mutations in the LaminA gene are the second most common inherited cause of Dilated Cardiomyopathy, a major form of heart failure. Here the authors show that disruption of the nuclear protein SUN1 in cardiomyocytes, by AAV mediated transduction of a S
Externí odkaz:
https://doaj.org/article/c8e8b6f93e7b442686a2d1ede70d7399
The swift advancement of large language models (LLMs) has profoundly shaped the landscape of artificial intelligence; however, their deployment in sensitive domains raises grave concerns, particularly due to their susceptibility to malicious exploita
Externí odkaz:
http://arxiv.org/abs/2408.15207
Large language models (LLMs) like ChatGPT and Gemini have significantly advanced natural language processing, enabling various applications such as chatbots and automated content generation. However, these models can be exploited by malicious individ
Externí odkaz:
http://arxiv.org/abs/2408.11727
This paper proposes a novel consensus-on-only-measurement distributed filter over directed graphs under the collectively observability condition. First, the distributed filter structure is designed with an augmented leader-following measurement fusio
Externí odkaz:
http://arxiv.org/abs/2408.06730
This paper offers a comprehensive performance analysis of the distributed continuous-time filtering in the presence of modeling errors. First, we introduce two performance indices, namely the nominal performance index and the estimation error covaria
Externí odkaz:
http://arxiv.org/abs/2408.06718
This paper systematically investigates the performance of consensus-based distributed filtering under mismatched noise covariances. First, we introduce three performance evaluation indices for such filtering problems,namely the standard performance e
Externí odkaz:
http://arxiv.org/abs/2408.06695
Autor:
Sun, Haoran, Jin, Renren, Xu, Shaoyang, Pan, Leiyu, Supryadi, Cui, Menglong, Du, Jiangcun, Lei, Yikun, Yang, Lei, Shi, Ling, Xiao, Juesi, Zhu, Shaolin, Xiong, Deyi
Large language models (LLMs) have demonstrated prowess in a wide range of tasks. However, many LLMs exhibit significant performance discrepancies between high- and low-resource languages. To mitigate this challenge, we present FuxiTranyu, an open-sou
Externí odkaz:
http://arxiv.org/abs/2408.06273
GlitchProber: Advancing Effective Detection and Mitigation of Glitch Tokens in Large Language Models
Autor:
Zhang, Zhibo, Bai, Wuxia, Li, Yuxi, Meng, Mark Huasong, Wang, Kailong, Shi, Ling, Li, Li, Wang, Jun, Wang, Haoyu
Large language models (LLMs) have achieved unprecedented success in the field of natural language processing. However, the black-box nature of their internal mechanisms has brought many concerns about their trustworthiness and interpretability. Recen
Externí odkaz:
http://arxiv.org/abs/2408.04905