Zobrazeno 1 - 10
of 368
pro vyhledávání: '"Xu, Mingze"'
This study explores the potential of Large Language Models (LLMs), specifically GPT-4, to enhance objectivity in organizational task performance evaluations. Through comparative analyses across two studies, including various task performance outputs,
Externí odkaz:
http://arxiv.org/abs/2408.05328
Autor:
Xu, Mingze, Gao, Mingfei, Gan, Zhe, Chen, Hong-You, Lai, Zhengfeng, Gang, Haiming, Kang, Kai, Dehghan, Afshin
We propose SlowFast-LLaVA (or SF-LLaVA for short), a training-free video large language model (LLM) that can jointly capture detailed spatial semantics and long-range temporal context without exceeding the token budget of commonly used LLMs. This is
Externí odkaz:
http://arxiv.org/abs/2407.15841
Autor:
Duan, Haodong, Xu, Mingze, Shuai, Bing, Modolo, Davide, Tu, Zhuowen, Tighe, Joseph, Bergamo, Alessandro
We present SkeleTR, a new framework for skeleton-based action recognition. In contrast to prior work, which focuses mainly on controlled environments, we target more general scenarios that typically involve a variable number of people and various for
Externí odkaz:
http://arxiv.org/abs/2309.11445
In this paper, we provide an in-depth study of Stochastic Backpropagation (SBP) when training deep neural networks for standard image classification and object detection tasks. During backward propagation, SBP calculates the gradients by only using a
Externí odkaz:
http://arxiv.org/abs/2210.00129
We propose an online tracking algorithm that performs the object detection and data association under a common framework, capable of linking objects after a long time span. This is realized by preserving a large spatio-temporal memory to store the id
Externí odkaz:
http://arxiv.org/abs/2203.16761
We propose a memory efficient method, named Stochastic Backpropagation (SBP), for training deep neural networks on videos. It is based on the finding that gradients from incomplete execution for backpropagation can still effectively train the models
Externí odkaz:
http://arxiv.org/abs/2203.16755
Publikováno v:
In Journal of Alloys and Compounds 15 October 2024 1002
Autor:
Li, Shilong, Cao, Jiaqi, Cheng, Xiangxin, Wang, Yiqun, Cao, Jun, Tang, Yueyuan, Liu, Yitao, Xu, Mingze, Li, Yuyu, Wei, Bin, Sun, Yang, Lu, Xueyi, Xie, Ming, Qian, Guoyu, Lu, Xia
Publikováno v:
In Nano Energy October 2024 129 Part A
Autor:
Sha, Qingrui, Sun, Kaicong, Jiang, Caiwen, Xu, Mingze, Xue, Zhong, Cao, Xiaohuan, Shen, Dinggang
Publikováno v:
In Neural Networks October 2024 178
Publikováno v:
In Neuroscience 16 August 2024 553:89-97