Zobrazeno 1 - 10
of 2 953
pro vyhledávání: '"Yu, Da"'
Autor:
Xie, Chulin, Huang, Yangsibo, Zhang, Chiyuan, Yu, Da, Chen, Xinyun, Lin, Bill Yuchen, Li, Bo, Ghazi, Badih, Kumar, Ravi
Large language models (LLMs) achieve good performance on challenging reasoning benchmarks, yet could also make basic reasoning mistakes. This contrasting behavior is puzzling when it comes to understanding the mechanisms behind LLMs' reasoning capabi
Externí odkaz:
http://arxiv.org/abs/2410.23123
Autor:
Xie, Chulin, Lin, Zinan, Backurs, Arturs, Gopi, Sivakanth, Yu, Da, Inan, Huseyin A, Nori, Harsha, Jiang, Haotian, Zhang, Huishuai, Lee, Yin Tat, Li, Bo, Yekhanin, Sergey
Text data has become extremely valuable due to the emergence of machine learning algorithms that learn from it. A lot of high-quality text data generated in the real world is private and therefore cannot be shared or used freely due to privacy concer
Externí odkaz:
http://arxiv.org/abs/2403.01749
Service providers of large language model (LLM) applications collect user instructions in the wild and use them in further aligning LLMs with users' intentions. These instructions, which potentially contain sensitive information, are annotated by hum
Externí odkaz:
http://arxiv.org/abs/2402.13659
Autor:
Caitlin Muhl, Kate Mulligan, Bogdan Chiva Giurca, Marie J. Polley, Gary Bloch, Dominik Alex Nowak, Charlotte Osborn-Forde, Sonia Hsiung, Kheng Hock Lee, Wolfram J. Herrmann, James Robert Baker, Dame Helen Jayne Stokes-Lampard, Sir Sam Everington, Michael Dixon, Isabelle Wachsmuth, Cristiano Figueiredo, Halfdan Thorsø Skjerning, Daniela Rojatz, Yu-Da Chen, Miriam L. Heijnders, Carolyn Wallace, Michelle Howarth, Daisuke Watanabe, Marcello Bertotti, Anu Helena Jansson, Susanna Althini, Felix Holzinger, Darren Glyn Dooler, Siân Brand, Tim James Anfilogoff, Daisy Fancourt, Michelle L. A. Nelson, Stephanie Tierney, Alison Leitch, Hae-Kweun Nam, Kiffer G. Card, Daniel Hayes, Siân Slade, Marie Anne Essam, Gay Anthia Palmer, Vivian Andrea Welch, David Robinson, Laurie Hilsgen, Niall Taylor, Rasmus Østergaard Nielsen, Dragana Vidovic, Emer Maeve McDaid, Louíse Viecili Hoffmeister, Jill Bonehill, Alan Siegel, Alžběta Bártová, David Acurio-Páez, Juan Manuel Mendive, Kerryn Husk
Publikováno v:
BMC Health Services Research, Vol 24, Iss 1, Pp 1-6 (2024)
Abstract Social prescribing has become a global phenomenon. A Delphi study was recently conducted with 48 social prescribing experts from 26 countries to establish global agreement on the definition of social prescribing. We reflect on the use and ut
Externí odkaz:
https://doaj.org/article/fc14aadaa76d4a36bc2e9e108b85c64a
Autor:
Yu, Da, Gopi, Sivakanth, Kulkarni, Janardhan, Lin, Zinan, Naik, Saurabh, Religa, Tomasz Lukasz, Yin, Jian, Zhang, Huishuai
Text prediction models, when used in applications like email clients or word processors, must protect user data privacy and adhere to model size constraints. These constraints are crucial to meet memory and inference time requirements, as well as to
Externí odkaz:
http://arxiv.org/abs/2305.13865
Autor:
Cummings, Rachel, Desfontaines, Damien, Evans, David, Geambasu, Roxana, Huang, Yangsibo, Jagielski, Matthew, Kairouz, Peter, Kamath, Gautam, Oh, Sewoong, Ohrimenko, Olga, Papernot, Nicolas, Rogers, Ryan, Shen, Milan, Song, Shuang, Su, Weijie, Terzis, Andreas, Thakurta, Abhradeep, Vassilvitskii, Sergei, Wang, Yu-Xiang, Xiong, Li, Yekhanin, Sergey, Yu, Da, Zhang, Huanyu, Zhang, Wanrong
In this article, we present a detailed review of current practices and state-of-the-art methodologies in the field of differential privacy (DP), with a focus of advancing DP's deployment in real-world applications. Key points and high-level contents
Externí odkaz:
http://arxiv.org/abs/2304.06929
Autor:
Du, Wan-Shun, Chen, Weipeng, Zhou, Yangbo, Zhou, Tengfei, Liu, Guangjian, Zhang, Zongteng, Miao, Zichuan, Jia, Hao, Liu, Song, Zhao, Yue, Zhang, Zhensheng, Chen, Tingyong, Wang, Ning, Huang, Wen, Tan, Zhen-Bing, Chen, Jing-Jing, Yu, Da-Peng
In the absence of time-reversal invariance, metals without inversion symmetry may exhibit nonreciprocal charge transport -- a magnetochiral anisotropy that manifests as unequal electrical resistance for opposite current flow directions. If supercondu
Externí odkaz:
http://arxiv.org/abs/2303.09052
Autor:
He, Jiyan, Li, Xuechen, Yu, Da, Zhang, Huishuai, Kulkarni, Janardhan, Lee, Yin Tat, Backurs, Arturs, Yu, Nenghai, Bian, Jiang
Differentially private deep learning has recently witnessed advances in computational efficiency and privacy-utility trade-off. We explore whether further improvements along the two axes are possible and provide affirmative answers leveraging two ins
Externí odkaz:
http://arxiv.org/abs/2212.01539
Publikováno v:
Frontiers in Pharmacology, Vol 15 (2024)
Rapid tissue reconstruction in acute and chronic injuries are challengeable, the inefficient repair mainly due to the difficulty in simultaneous promoting the regeneration of peripheral nerves and vascular, which are closely related. Main clinical me
Externí odkaz:
https://doaj.org/article/80e349a59cf440058c1f53cd0e82edae
Publikováno v:
BMC Anesthesiology, Vol 24, Iss 1, Pp 1-8 (2024)
Abstract Objective The aim of this study is to observe the anesthetic effect and safety of intravenous anesthesia without muscle relaxant with propofol-remifentanil combined with regional block under laryngeal mask airway in pediatric ophthalmologic
Externí odkaz:
https://doaj.org/article/2d4c127b573549a9a14ed4ed4021e66b