Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Anderson Taíra"'
Autor:
Lais Renata Almeida Cezário, Gláucia Maria Bovi Ambrosano, Guilherme Bovi Ambrosano, Anderson Taíra, Rosana de Fátima Possobon, Marcelo de Castro Meneghim, Karine Laura Cortellazzi
Publikováno v:
Bioscience Journal, Vol 40, Pp e40031-e40031 (2024)
This cross-sectional study aimed to assess whether levels of anxiety, perceived stress, and self-perception of happiness during the Covid-19 pandemic were lower among Tai Chi (TC) practitioners. An online questionnaire was applied from September 2020
Externí odkaz:
https://doaj.org/article/a6e4f68e934a4e1187dcb59115848300
Autor:
Laís Renata Almeida Cezário, Gláucia Maria Bovi Ambrosano, Guilherme Bovi Ambrosano, Anderson Taíra, Rosana de Fátima Possobon, Marcelo de Castro Meneghim, Karine Laura Cortellazzi
Publikováno v:
Bioscience Journal, Vol 39, Pp e39079-e39079 (2023)
This intervention follow-up study evaluated anxiety and stress levels and self-perceived happiness of individuals linked to the health field who did not practice Tai Chi and compared these variables before and after practicing this art. One hundred t
Externí odkaz:
https://doaj.org/article/9681bc1e845f4e86a7aa314c28285358
Autor:
Deitke, Matt, Clark, Christopher, Lee, Sangho, Tripathi, Rohun, Yang, Yue, Park, Jae Sung, Salehi, Mohammadreza, Muennighoff, Niklas, Lo, Kyle, Soldaini, Luca, Lu, Jiasen, Anderson, Taira, Bransom, Erin, Ehsani, Kiana, Ngo, Huong, Chen, YenSung, Patel, Ajay, Yatskar, Mark, Callison-Burch, Chris, Head, Andrew, Hendrix, Rose, Bastani, Favyen, VanderBilt, Eli, Lambert, Nathan, Chou, Yvonne, Chheda, Arnavi, Sparks, Jenna, Skjonsberg, Sam, Schmitz, Michael, Sarnat, Aaron, Bischoff, Byron, Walsh, Pete, Newell, Chris, Wolters, Piper, Gupta, Tanmay, Zeng, Kuo-Hao, Borchardt, Jon, Groeneveld, Dirk, Dumas, Jen, Nam, Crystal, Lebrecht, Sophie, Wittlif, Caitlin, Schoenick, Carissa, Michel, Oscar, Krishna, Ranjay, Weihs, Luca, Smith, Noah A., Hajishirzi, Hannaneh, Girshick, Ross, Farhadi, Ali, Kembhavi, Aniruddha
Today's most advanced multimodal models remain proprietary. The strongest open-weight models rely heavily on synthetic data from proprietary VLMs to achieve good performance, effectively distilling these closed models into open ones. As a result, the
Externí odkaz:
http://arxiv.org/abs/2409.17146
