Zobrazeno 1 - 10
of 160
pro vyhledávání: '"Zhu, Alan"'
Autor:
Zhu, Alan Y.
In the era of hardware specialization, field-programmable gate arrays (FPGAs) provide a promising platform for computer architects, combining the programmability of software with the speed and performance of hardware. Despite this, compiling hardware
Autor:
Chen, Valerie, Zhu, Alan, Zhao, Sebastian, Mozannar, Hussein, Sontag, David, Talwalkar, Ameet
While current chat-based AI assistants primarily operate reactively, responding only when prompted by users, there is significant potential for these systems to proactively assist in tasks without explicit invocation, enabling a mixed-initiative inte
Externí odkaz:
http://arxiv.org/abs/2410.04596
Autor:
Zhang, Zhihao, Zhu, Alan, Yang, Lijie, Xu, Yihua, Li, Lanting, Phothilimthana, Phitchaya Mangpo, Jia, Zhihao
Retrieval-augmented language models (RaLM) have demonstrated the potential to solve knowledge-intensive natural language processing (NLP) tasks by combining a non-parametric knowledge base with a parametric language model. Instead of fine-tuning a fu
Externí odkaz:
http://arxiv.org/abs/2401.14021
Autor:
Zhu, Alan
These poems of vulnerability, love, and loss trace the journey of a poet slowly coming into their identity. They emphasize the intensity and quality of the mundane, with poems found in bus stops, bowls of soup, quiet mornings, and inkstains. The repe
Externí odkaz:
https://hdl.handle.net/1721.1/151291
TreeScope: An Agricultural Robotics Dataset for LiDAR-Based Mapping of Trees in Forests and Orchards
Autor:
Cheng, Derek, Ojeda, Fernando Cladera, Prabhu, Ankit, Liu, Xu, Zhu, Alan, Green, Patrick Corey, Ehsani, Reza, Chaudhari, Pratik, Kumar, Vijay
Data collection for forestry, timber, and agriculture currently relies on manual techniques which are labor-intensive and time-consuming. We seek to demonstrate that robotics offers improvements over these techniques and accelerate agricultural resea
Externí odkaz:
http://arxiv.org/abs/2310.02162
Autor:
Miao, Xupeng, Oliaro, Gabriele, Zhang, Zhihao, Cheng, Xinhao, Wang, Zeyu, Zhang, Zhengxin, Wong, Rae Ying Yee, Zhu, Alan, Yang, Lijie, Shi, Xiaoxiang, Shi, Chunan, Chen, Zhuoming, Arfeen, Daiyaan, Abhyankar, Reyna, Jia, Zhihao
This paper introduces SpecInfer, a system that accelerates generative large language model (LLM) serving with tree-based speculative inference and verification. The key idea behind SpecInfer is leveraging small speculative models to predict the LLM's
Externí odkaz:
http://arxiv.org/abs/2305.09781
Autor:
Wang, Yao, Zhou, Jiaxin, Yang, Qi, Li, Xinmeng, Qiu, Yifu, Zhang, Yansong, Liu, Min, Zhu, Alan Jian
Publikováno v:
In Journal of Lipid Research October 2024 65(10)
Autor:
Zhu, Alan, Patel, Bhavika K., Khurana, Aditya, Maxwell, Robert W., Ellis, Richard L., Fazzio, Robert T., Sharpe, Richard E., Jr.
Publikováno v:
In Journal of the American College of Radiology July 2024 21(7):993-1000
Publikováno v:
In Clinical and Translational Radiation Oncology January 2024 44
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.