Zobrazeno 1 - 10
of 53 342
pro vyhledávání: '"chen, jie"'
Autor:
Min, Yingqian, Chen, Zhipeng, Jiang, Jinhao, Chen, Jie, Deng, Jia, Hu, Yiwen, Tang, Yiru, Wang, Jiapeng, Cheng, Xiaoxue, Song, Huatong, Zhao, Wayne Xin, Liu, Zheng, Wang, Zhongyuan, Wen, Ji-Rong
Recently, slow-thinking reasoning systems, such as o1, have demonstrated remarkable capabilities in solving complex reasoning tasks. These systems typically engage in an extended thinking process before responding to a query, allowing them to generat
Externí odkaz:
http://arxiv.org/abs/2412.09413
Deep neural networks (DNNs) are vulnerable to adversarial samples crafted by adding imperceptible perturbations to clean data, potentially leading to incorrect and dangerous predictions. Adversarial purification has been an effective means to improve
Externí odkaz:
http://arxiv.org/abs/2412.08394
With increasing numbers of vulnerabilities exposed on the internet, autonomous penetration testing (pentesting) has emerged as an emerging research area, while reinforcement learning (RL) is a natural fit for studying autonomous pentesting. Previous
Externí odkaz:
http://arxiv.org/abs/2412.04078
Autor:
Gao, Qiankun, Wu, Yanmin, Wen, Chengxiang, Meng, Jiarui, Tang, Luyang, Chen, Jie, Wang, Ronggang, Zhang, Jian
Reconstructing dynamic scenes with large-scale and complex motions remains a significant challenge. Recent techniques like Neural Radiance Fields and 3D Gaussian Splatting (3DGS) have shown promise but still struggle with scenes involving substantial
Externí odkaz:
http://arxiv.org/abs/2412.02493
Autor:
Zheng, Youqiang, Tu, Weiping, Kang, Yueteng, Chen, Jie, Zhang, Yike, Xiao, Li, Yang, Yuhong, Ma, Long
Neural speech codecs have gained great attention for their outstanding reconstruction with discrete token representations. It is a crucial component in generative tasks such as speech coding and large language models (LLM). However, most works based
Externí odkaz:
http://arxiv.org/abs/2412.01053
Autor:
Lu, Yue, Chen, Jie, Zhou, Feng, Lau, Yong-Chang, Wisniewski, Piotr, Kaczorowski, Dariusz, Xi, Xue-Kui, Wang, Wen-Hong
The angular dependence of magnetoresistance (MR) in antiferromagnetic half-Heusler HoAuSn single crystals have been systematically studied. Negative MR, as large as 99%, is observed at 9 T, is not restricted to the specific configuration of applied m
Externí odkaz:
http://arxiv.org/abs/2411.14140
Graph contrastive learning (GCL) has shown promising performance in semisupervised graph classification. However, existing studies still encounter significant challenges in GCL. First, successive layers in graph neural network (GNN) tend to produce m
Externí odkaz:
http://arxiv.org/abs/2411.15206
Real-world image super-resolution (Real-ISR) aims to reconstruct high-resolution images from low-resolution inputs degraded by complex, unknown processes. While many Stable Diffusion (SD)-based Real-ISR methods have achieved remarkable success, their
Externí odkaz:
http://arxiv.org/abs/2411.13383
Autor:
Jiang, Jinhao, Chen, Zhipeng, Min, Yingqian, Chen, Jie, Cheng, Xiaoxue, Wang, Jiapeng, Tang, Yiru, Sun, Haoxiang, Deng, Jia, Zhao, Wayne Xin, Liu, Zheng, Yan, Dong, Xie, Jian, Wang, Zhongyuan, Wen, Ji-Rong
Recently, test-time scaling has garnered significant attention from the research community, largely due to the substantial advancements of the o1 model released by OpenAI. By allocating more computational resources during the inference phase, large l
Externí odkaz:
http://arxiv.org/abs/2411.11694
In this paper, we continue the study of the local well-posedness theory for the Schr\"{o}dinger-KdV system in the Sobolev space $H^{s_1}\times H^{s_2}$. We show the local well-posedness in $H^{-3/16}\times H^{-3/4}$ for $\beta = 0$. Combining our wor
Externí odkaz:
http://arxiv.org/abs/2411.10977