Zobrazeno 1 - 10
of 8 804
pro vyhledávání: '"Wang XUN"'
Autor:
ZHANG Junhu, LIANG Chunhao, DENG Cunbao, GUO Hui, GUO Xiaoyang, WANG Xun, YANG Bo, ZHANG Mingqi
Publikováno v:
Meikuang Anquan, Vol 54, Iss 2, Pp 15-21 (2023)
In order to study the influence of the chemical structure of coal measure rock on the gas adsorption performance, taking the coal and rock samples of Shaqu No.1 Mine as the research object, the structure of coal and rock was analyzed from the microsc
Externí odkaz:
https://doaj.org/article/4d5e601bba724ce4a47b1047979b75c7
Autor:
WANG Yu, WANG Suyue, JIN Ping, ZHU Yulong, XIA Kun, SUN Dandan, AI Wenlong, FU Xiaoming, YE Qunrong, LI Kai, WANG Xun
Publikováno v:
罕见病研究, Vol 1, Iss 2, Pp 189-195 (2022)
O'Sullivan-Mcleod syndrome is a very rare variant of MND with a good prognosis. Its clinical feature is distal lower motor neuron syndrome of both upper limbs, and there is no effective treatment at present. We reported a case of O'Sullivan-Mcleod sy
Externí odkaz:
https://doaj.org/article/c671e78f7f3a406381c04feae16daa42
Autor:
Li, Siyuan, Ma, Zhe, Liu, Feifan, Lu, Jiani, Xiao, Qinqin, Sun, Kewu, Cui, Lingfei, Yang, Xirui, Liu, Peng, Wang, Xun
Robot task planning is an important problem for autonomous robots in long-horizon challenging tasks. As large pre-trained models have demonstrated superior planning ability, recent research investigates utilizing large models to achieve autonomous pl
Externí odkaz:
http://arxiv.org/abs/2411.06920
Offline-to-Online Reinforcement Learning has emerged as a powerful paradigm, leveraging offline data for initialization and online fine-tuning to enhance both sample efficiency and performance. However, most existing research has focused on single-ag
Externí odkaz:
http://arxiv.org/abs/2410.19450
Autor:
Liu, Yanming, Peng, Xinyue, Cao, Jiannan, Bo, Shi, Shen, Yanxin, Zhang, Xuhong, Cheng, Sheng, Wang, Xun, Yin, Jianwei, Du, Tianyu
Large language models (LLMs) have shown remarkable capabilities in natural language processing; however, they still face difficulties when tasked with understanding lengthy contexts and executing effective question answering. These challenges often a
Externí odkaz:
http://arxiv.org/abs/2410.01671
Autor:
Zhang, Boyu, Du, Tianyu, Tong, Junkai, Zhang, Xuhong, Chow, Kingsum, Cheng, Sheng, Wang, Xun, Yin, Jianwei
After large models (LMs) have gained widespread acceptance in code-related tasks, their superior generative capacity has greatly promoted the application of the code LM. Nevertheless, the security of the generated code has raised attention to its pot
Externí odkaz:
http://arxiv.org/abs/2410.01488
The rapid development of Large Language Models (LLMs) has brought remarkable generative capabilities across diverse tasks. However, despite the impressive achievements, these LLMs still have numerous inherent vulnerabilities, particularly when faced
Externí odkaz:
http://arxiv.org/abs/2407.16205
Autor:
Wang, Song, Wang, Xun, Mei, Jie, Xie, Yujia, Muarray, Sean, Li, Zhang, Wu, Lingfeng, Chen, Si-Qing, Xiong, Wayne
Hallucination, a phenomenon where large language models (LLMs) produce output that is factually incorrect or unrelated to the input, is a major challenge for LLM applications that require accuracy and dependability. In this paper, we introduce a reli
Externí odkaz:
http://arxiv.org/abs/2407.15441
Publikováno v:
Cailiao gongcheng, Vol 48, Iss 6, Pp 125-131 (2020)
Recycling is the most effective way to dispose of waste polymer materials. It can not only reduce the harm of polymer materials to the natural environment, but also achieve the purpose of saving cost and turning waste into treasure. A self-made melt
Externí odkaz:
https://doaj.org/article/950eeafef3c34039bf26329ac6be097d
Publikováno v:
Open Medicine, Vol 15, Iss 1, Pp 190-197 (2020)
Lung cancer is one of the most harmful malignant tumors to human health. The accurate judgment of the pathological type of lung cancer is vital for treatment. Traditionally, the pathological type of lung cancer requires a histopathological examinatio
Externí odkaz:
https://doaj.org/article/f33f7b7304fc4eefa3b3ef5bc143963d