Zobrazeno 1 - 10
of 154
pro vyhledávání: '"Zhao Jiachen"'
Publikováno v:
Open Life Sciences, Vol 18, Iss 1, Pp 3272-87 (2023)
This study aimed to explore the effects of tissue inhibitor of metalloproteinases‐1 (TIMP‐1) on levocarnitine (LC)-mediated regulation of angiotensin II (AngII)-induced myocardial fibrosis (MF) and its underlying mechanisms. H9C2 cells were treat
Externí odkaz:
https://doaj.org/article/ab943acf3af349b2b0f417e28d177b78
Autor:
Hu Yunpeng, Feng Wenkai, Li Wenbin, Yi Xiaoyu, Liu Kan, Ye Longzhen, Zhao Jiachen, Lu Xianjing, Zhang Ruichao
Publikováno v:
Reviews on Advanced Materials Science, Vol 62, Iss 1, Pp pp. 243-251 (2023)
The roughness of the joint surface plays a significant role in evaluating the shear strength of rock. The waviness (first-order) and unevenness (second-order) of natural joints have different effects on the characterization of joint surface roughness
Externí odkaz:
https://doaj.org/article/d6ba63e1490d4b6f9a0383f2e53f19b2
Autor:
Jin, Yitong, Qiu, Zhiping, Shi, Yi, Sun, Shuangpeng, Wang, Chongwu, Pan, Donghao, Zhao, Jiachen, Liang, Zhenghao, Wang, Yuan, Li, Xiaobing, Yu, Feng, Yu, Tao, Dai, Qionghai
In this paper, we touch on the problem of markerless multi-modal human motion capture especially for string performance capture which involves inherently subtle hand-string contacts and intricate movements. To fulfill this goal, we first collect a da
Externí odkaz:
http://arxiv.org/abs/2405.04963
Autor:
Li, Hongwei Bran, Navarro, Fernando, Ezhov, Ivan, Bayat, Amirhossein, Das, Dhritiman, Kofler, Florian, Shit, Suprosanna, Waldmannstetter, Diana, Paetzold, Johannes C., Hu, Xiaobin, Wiestler, Benedikt, Zimmer, Lucas, Amiranashvili, Tamaz, Prabhakar, Chinmay, Berger, Christoph, Weidner, Jonas, Alonso-Basant, Michelle, Rashid, Arif, Baid, Ujjwal, Adel, Wesam, Ali, Deniz, Baheti, Bhakti, Bai, Yingbin, Bhatt, Ishaan, Cetindag, Sabri Can, Chen, Wenting, Cheng, Li, Dutand, Prasad, Dular, Lara, Elattar, Mustafa A., Feng, Ming, Gao, Shengbo, Huisman, Henkjan, Hu, Weifeng, Innani, Shubham, Jiat, Wei, Karimi, Davood, Kuijf, Hugo J., Kwak, Jin Tae, Le, Hoang Long, Lia, Xiang, Lin, Huiyan, Liu, Tongliang, Ma, Jun, Ma, Kai, Ma, Ting, Oksuz, Ilkay, Holland, Robbie, Oliveira, Arlindo L., Pal, Jimut Bahan, Pei, Xuan, Qiao, Maoying, Saha, Anindo, Selvan, Raghavendra, Shen, Linlin, Silva, Joao Lourenco, Spiclin, Ziga, Talbar, Sanjay, Wang, Dadong, Wang, Wei, Wang, Xiong, Wang, Yin, Xia, Ruiling, Xu, Kele, Yan, Yanwu, Yergin, Mert, Yu, Shuang, Zeng, Lingxi, Zhang, YingLin, Zhao, Jiachen, Zheng, Yefeng, Zukovec, Martin, Do, Richard, Becker, Anton, Simpson, Amber, Konukoglu, Ender, Jakab, Andras, Bakas, Spyridon, Joskowicz, Leo, Menze, Bjoern
Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a significant challenge in achieving consistent and reliable image segmentat
Externí odkaz:
http://arxiv.org/abs/2405.18435
Autor:
Unnikrishnan, Govind, Ilzhöfer, Philipp, Scholz, Achim, Hölzl, Christian, Götzelmann, Aaron, Gupta, Ratnesh Kumar, Zhao, Jiachen, Krauter, Jennifer, Weber, Sebastian, Makki, Nastasia, Büchler, Hans Peter, Pfau, Tilman, Meinert, Florian
Publikováno v:
Phys. Rev. Lett. 132, 150606 (2024)
We report on the first realization of a novel neutral atom qubit encoded in the metastable fine-structure states ${^3\rm{P}_0}$ and ${^3\rm{P}_2}$ of single $^{88}$Sr atoms trapped in an optical tweezer. Raman coupling of the qubit states promises ra
Externí odkaz:
http://arxiv.org/abs/2401.10679
As the number of large language models (LLMs) released to the public grows, there is a pressing need to understand the safety implications associated with these models learning from third-party custom finetuning data. We explore the behavior of LLMs
Externí odkaz:
http://arxiv.org/abs/2312.12736
Autor:
Zhao, Jiachen
Knowledge distillation (KD) has been widely employed to transfer knowledge from a large language model (LLM) to a specialized model in low-data regimes through pseudo label learning. However, pseudo labels generated by teacher models are usually nois
Externí odkaz:
http://arxiv.org/abs/2312.10185
Autor:
Zhao, Jiachen, Zhao, Wenlong, Drozdov, Andrew, Rozonoyer, Benjamin, Sultan, Md Arafat, Lee, Jay-Yoon, Iyyer, Mohit, McCallum, Andrew
We study semi-supervised sequence generation tasks, where the few labeled examples are too scarce to finetune a model, and meanwhile, few-shot prompted large language models (LLMs) exhibit room for improvement. In this paper, we present the discovery
Externí odkaz:
http://arxiv.org/abs/2311.08640
In this work, we study in-context teaching (ICT), where a teacher provides in-context example rationales to teach a student to reason over unseen cases. Human teachers are usually required to craft in-context demonstrations, which are costly and have
Externí odkaz:
http://arxiv.org/abs/2311.06985
Autor:
Zhao, Jiachen
Recently, large language models (LLMs) have made remarkable progress in natural language processing. The most representative ability of LLMs is in-context learning (ICL), which enables LLMs to learn patterns from in-context exemplars without training
Externí odkaz:
http://arxiv.org/abs/2311.03498