Zobrazeno 1 - 10
of 20 165
pro vyhledávání: '"Sun, Yi"'
Reinforcement learning method is extremely competitive in gait generation techniques for quadrupedal robot, which is mainly due to the fact that stochastic exploration in reinforcement training is beneficial to achieve an autonomous gait. Nevertheles
Externí odkaz:
http://arxiv.org/abs/2409.16862
Estimation of a model's confidence on its outputs is critical for Conversational AI systems based on large language models (LLMs), especially for reducing hallucination and preventing over-reliance. In this work, we provide an exhaustive exploration
Externí odkaz:
http://arxiv.org/abs/2409.09629
Autor:
Gao, Lin, Lu, Jing, Shao, Zekai, Lin, Ziyue, Yue, Shengbin, Ieong, Chiokit, Sun, Yi, Zauner, Rory James, Wei, Zhongyu, Chen, Siming
Large Language Models (LLMs) have shown great potential in intelligent visualization systems, especially for domain-specific applications. Integrating LLMs into visualization systems presents challenges, and we categorize these challenges into three
Externí odkaz:
http://arxiv.org/abs/2407.20570
Autor:
Sun, Yi
The family of local maximum likelihood (LML) detectors, including the global maximum likelihood (GML) detector, and the family of likelihood ascent search (LAS) detectors are akin to each other and possess common properties significant in both theory
Externí odkaz:
http://arxiv.org/abs/2407.19709
Autor:
Wang, Licheng, Qureshi, Ali Hamza, Sun, Yi, Xu, Xiaokang, Yao, Xiaojing, Zhao, Xinli, He, Ai-Lei, Zhou, Yuan, Zhang, Xiuyun
As the novel topological states, the higher-order topological insulators have attracted great attentions in the past years. However, their realizations in realistic materials, in particular in two dimensional systems, remains the big challenge due to
Externí odkaz:
http://arxiv.org/abs/2407.10432
Autor:
Du, Changde, Fu, Kaicheng, Wen, Bincheng, Sun, Yi, Peng, Jie, Wei, Wei, Gao, Ying, Wang, Shengpei, Zhang, Chuncheng, Li, Jinpeng, Qiu, Shuang, Chang, Le, He, Huiguang
The conceptualization and categorization of natural objects in the human mind have long intrigued cognitive scientists and neuroscientists, offering crucial insights into human perception and cognition. Recently, the rapid development of Large Langua
Externí odkaz:
http://arxiv.org/abs/2407.01067
Solving partial differential equations (PDEs) and their inverse problems using Physics-informed neural networks (PINNs) is a rapidly growing approach in the physics and machine learning community. Although several architectures exist for PINNs that w
Externí odkaz:
http://arxiv.org/abs/2406.14808
The ability to automatically and robustly self-verify periodicity present in time-series astronomical data is becoming more important as data sets rapidly increase in size. The age of large astronomical surveys has rendered manual inspection of time-
Externí odkaz:
http://arxiv.org/abs/2406.08571
The perception of transparent objects for grasp and manipulation remains a major challenge, because existing robotic grasp methods which heavily rely on depth maps are not suitable for transparent objects due to their unique visual properties. These
Externí odkaz:
http://arxiv.org/abs/2405.15299
Generating grasps for a dexterous hand often requires numerous grasping annotations. However, annotating high DoF dexterous hand poses is quite challenging. Especially for functional grasps, the grasp pose must be convenient for subsequent manipulati
Externí odkaz:
http://arxiv.org/abs/2405.08310