Zobrazeno 1 - 10
of 452
pro vyhledávání: '"Gao, Yifei"'
Autor:
Feng, Shiwei, Chen, Xuan, Cheng, Zhiyuan, Xiong, Zikang, Gao, Yifei, Cheng, Siyuan, Kate, Sayali, Zhang, Xiangyu
Robot navigation is increasingly crucial across applications like delivery services and warehouse management. The integration of Reinforcement Learning (RL) with classical planning has given rise to meta-planners that combine the adaptability of RL w
Externí odkaz:
http://arxiv.org/abs/2409.10832
Large Language Models (LLMs) showcase remarkable performance and robust deductive capabilities, yet their expansive size complicates deployment and raises environmental concerns due to substantial resource consumption. The recent development of a qua
Externí odkaz:
http://arxiv.org/abs/2407.15508
Emergent Large Language Models (LLMs) use their extraordinary performance and powerful deduction capacity to discern from traditional language models. However, the expenses of computational resources and storage for these LLMs are stunning, quantizat
Externí odkaz:
http://arxiv.org/abs/2406.16299
Recent developments in neural rendering techniques have greatly enhanced the rendering of photo-realistic 3D scenes across both academic and commercial fields. The latest method, known as 3D Gaussian Splatting (3D-GS), has set new benchmarks for rend
Externí odkaz:
http://arxiv.org/abs/2404.18669
The evolution of Artificial Intelligence Generated Contents (AIGCs) is advancing towards higher quality. The growing interactions with AIGCs present a new challenge to the data-driven AI community: While AI-generated contents have played a crucial ro
Externí odkaz:
http://arxiv.org/abs/2403.08542
In the fundamental statistics course, students are taught to remember the well-known saying: "Correlation is not Causation". Till now, statistics (i.e., correlation) have developed various successful frameworks, such as Transformer and Pre-training l
Externí odkaz:
http://arxiv.org/abs/2311.12307
Recently, with the emergence of numerous Large Language Models (LLMs), the implementation of AI has entered a new era. Irrespective of these models' own capacity and structure, there is a growing demand for LLMs to possess enhanced comprehension of l
Externí odkaz:
http://arxiv.org/abs/2307.13365
Adversarial example detection is known to be an effective adversarial defense method. Black-box attack, which is a more realistic threat and has led to various black-box adversarial training-based defense methods, however, does not attract considerab
Externí odkaz:
http://arxiv.org/abs/2306.02021
Autor:
Dong, Yinpeng, Chen, Peng, Deng, Senyou, L, Lianji, Sun, Yi, Zhao, Hanyu, Li, Jiaxing, Tan, Yunteng, Liu, Xinyu, Dong, Yangyi, Xu, Enhui, Xu, Jincai, Xu, Shu, Fu, Xuelin, Sun, Changfeng, Han, Haoliang, Zhang, Xuchong, Chen, Shen, Sun, Zhimin, Cao, Junyi, Yao, Taiping, Ding, Shouhong, Wu, Yu, Lin, Jian, Wu, Tianpeng, Wang, Ye, Fu, Yu, Feng, Lin, Gao, Kangkang, Liu, Zeyu, Pang, Yuanzhe, Duan, Chengqi, Zhou, Huipeng, Wang, Yajie, Zhao, Yuhang, Wu, Shangbo, Lyu, Haoran, Lin, Zhiyu, Gao, Yifei, Li, Shuang, Wang, Haonan, Sang, Jitao, Ma, Chen, Zheng, Junhao, Li, Yijia, Shen, Chao, Lin, Chenhao, Cui, Zhichao, Liu, Guoshuai, Shi, Huafeng, Hu, Kun, Zhang, Mengxin
The security of artificial intelligence (AI) is an important research area towards safe, reliable, and trustworthy AI systems. To accelerate the research on AI security, the Artificial Intelligence Security Competition (AISC) was organized by the Zho
Externí odkaz:
http://arxiv.org/abs/2212.03412
CNNs exhibit many behaviors different from humans, one of which is the capability of employing high-frequency components. This paper discusses the frequency bias phenomenon in image classification tasks: the high-frequency components are actually muc
Externí odkaz:
http://arxiv.org/abs/2205.03154