Zobrazeno 1 - 10
of 1 530
pro vyhledávání: '"Liu Jiacheng"'
Autor:
Liu, Jiacheng, Tang, Peng, Wang, Wenfeng, Ren, Yuhang, Hou, Xiaofeng, Heng, Pheng-Ann, Guo, Minyi, Li, Chao
The emergence of large-scale Mixture of Experts (MoE) models has marked a significant advancement in artificial intelligence, offering enhanced model capacity and computational efficiency through conditional computation. However, the deployment and i
Externí odkaz:
http://arxiv.org/abs/2412.14219
Autor:
Liu, Jiacheng, Li, Yuanchun, Li, Liangyan, Sun, Yi, Wen, Hao, Li, Xiangyu, Guo, Yao, Liu, Yunxin
Many applications demand context sensing to offer personalized and timely services. Yet, developing sensing programs can be challenging for developers and using them is privacy-concerning for end-users. In this paper, we propose to use natural langua
Externí odkaz:
http://arxiv.org/abs/2412.15240
Autor:
Bhagia, Akshita, Liu, Jiacheng, Wettig, Alexander, Heineman, David, Tafjord, Oyvind, Jha, Ananya Harsh, Soldaini, Luca, Smith, Noah A., Groeneveld, Dirk, Koh, Pang Wei, Dodge, Jesse, Hajishirzi, Hannaneh
We develop task scaling laws and model ladders to predict the individual task performance of pretrained language models (LMs) in the overtrained setting. Standard power laws for language modeling loss cannot accurately model task performance. Therefo
Externí odkaz:
http://arxiv.org/abs/2412.04403
Autor:
Song, Yuheng, Cui, Jiayuan, Liu, Guohao, Zhao, Jiabiao, Zhang, Mingxia, Liu, Jiacheng, Li, Da, Li, Peian, Yao, Chen, Song, Fei, Liang, Hong, Ma, Jianjun
Terahertz (THz) communications have emerged as a promising technology for 6G networks due to their potential for achieving terabit-per-second data rates. However, the impact of rainfall on THz channel characteristics remains incompletely understood,
Externí odkaz:
http://arxiv.org/abs/2412.03916
In-hospital mortality (IHM) prediction for ICU patients is critical for timely interventions and efficient resource allocation. While structured physiological data provides quantitative insights, clinical notes offer unstructured, context-rich narrat
Externí odkaz:
http://arxiv.org/abs/2411.16818
Autor:
Tang, Peng, Liu, Jiacheng, Hou, Xiaofeng, Pu, Yifei, Wang, Jing, Heng, Pheng-Ann, Li, Chao, Guo, Minyi
The Mixture-of-Experts (MoE) architecture has demonstrated significant advantages in the era of Large Language Models (LLMs), offering enhanced capabilities with reduced inference costs. However, deploying MoE-based LLMs on memoryconstrained edge dev
Externí odkaz:
http://arxiv.org/abs/2411.01433
Autor:
Lu, Ximing, Sclar, Melanie, Hallinan, Skyler, Mireshghallah, Niloofar, Liu, Jiacheng, Han, Seungju, Ettinger, Allyson, Jiang, Liwei, Chandu, Khyathi, Dziri, Nouha, Choi, Yejin
Creativity has long been considered one of the most difficult aspect of human intelligence for AI to mimic. However, the rise of Large Language Models (LLMs), like ChatGPT, has raised questions about whether AI can match or even surpass human creativ
Externí odkaz:
http://arxiv.org/abs/2410.04265
Autor:
Tan, Dongjie, Ji, Jianghui, Bao, Chunhui, Huang, Xiumin, Chen, Guo, Wang, Su, Dong, Yao, Li, Haitao, Zhang, Junbo, Fang, Liang, Li, Dong, Deng, Lei, Liu, Jiacheng, Zhu, Zi
The Closeby Habitable Exoplanet Survey (CHES) constitutes a mission intricately designed to systematically survey approximately 100 solar-type stars located within the immediate proximity of the solar system, specifically within a range of 10 parsecs
Externí odkaz:
http://arxiv.org/abs/2408.06338
Autor:
Wu, Jiahao, Liu, Jiacheng, Ren, Zheyu, Leung, Man Yin, Leung, Wai Kuen, Ho, Kin On, Wang, Xiangrong, Shao, Qiming, Yang, Sen
Publikováno v:
npj Spintronics volume 2, Article number: 30 (2024)
Frequency conversion is a widely realized physical process in nonlinear systems of optics and electronics. As an emerging nonlinear platform, spintronic devices have the potential to achieve stronger frequency conversion. Here, we demonstrated a micr
Externí odkaz:
http://arxiv.org/abs/2407.03201
Autor:
Ivison, Hamish, Wang, Yizhong, Liu, Jiacheng, Wu, Zeqiu, Pyatkin, Valentina, Lambert, Nathan, Smith, Noah A., Choi, Yejin, Hajishirzi, Hannaneh
Learning from preference feedback has emerged as an essential step for improving the generation quality and performance of modern language models (LMs). Despite its widespread use, the way preference-based learning is applied varies wildly, with diff
Externí odkaz:
http://arxiv.org/abs/2406.09279