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pro vyhledávání: '"Zhao, Huaqin"'
Autor:
Li, Yiwei, Wu, Zihao, Zhao, Huaqin, Yang, Tianze, Liu, Zhengliang, Shu, Peng, Sun, Jin, Parasuraman, Ramviyas, Liu, Tianming
To tackle the "reality gap" encountered in Sim-to-Real transfer, this study proposes a diffusion-based framework that minimizes inconsistencies in grasping actions between the simulation settings and realistic environments. The process begins by trai
Externí odkaz:
http://arxiv.org/abs/2403.11459
Autor:
Xu, Shaochen, Wu, Zihao, Zhao, Huaqin, Shu, Peng, Liu, Zhengliang, Liao, Wenxiong, Li, Sheng, Sikora, Andrea, Liu, Tianming, Li, Xiang
In this study, we leverage LLM to enhance the semantic analysis and develop similarity metrics for texts, addressing the limitations of traditional unsupervised NLP metrics like ROUGE and BLEU. We develop a framework where LLMs such as GPT-4 are empl
Externí odkaz:
http://arxiv.org/abs/2402.11398
Autor:
Shu, Peng, Zhao, Huaqin, Jiang, Hanqi, Li, Yiwei, Xu, Shaochen, Pan, Yi, Wu, Zihao, Liu, Zhengliang, Lu, Guoyu, Guan, Le, Chen, Gong, Liu, Xianqiao Wang Tianming
Large language models and multimodal large language models have revolutionized artificial intelligence recently. An increasing number of regions are now embracing these advanced technologies. Within this context, robot coding education is garnering i
Externí odkaz:
http://arxiv.org/abs/2402.06116
Autor:
Zhao, Huaqin, Liu, Zhengliang, Wu, Zihao, Li, Yiwei, Yang, Tianze, Shu, Peng, Xu, Shaochen, Dai, Haixing, Zhao, Lin, Mai, Gengchen, Liu, Ninghao, Liu, Tianming
In recent years, Large Language Models (LLMs) like ChatGPT have seen considerable advancements and have been applied in diverse fields. Built on the Transformer architecture, these models are trained on extensive datasets, enabling them to understand
Externí odkaz:
http://arxiv.org/abs/2401.11641
Autor:
Wang, Jiaqi, Wu, Zihao, Li, Yiwei, Jiang, Hanqi, Shu, Peng, Shi, Enze, Hu, Huawen, Ma, Chong, Liu, Yiheng, Wang, Xuhui, Yao, Yincheng, Liu, Xuan, Zhao, Huaqin, Liu, Zhengliang, Dai, Haixing, Zhao, Lin, Ge, Bao, Li, Xiang, Liu, Tianming, Zhang, Shu
Large language models (LLMs) have undergone significant expansion and have been increasingly integrated across various domains. Notably, in the realm of robot task planning, LLMs harness their advanced reasoning and language comprehension capabilitie
Externí odkaz:
http://arxiv.org/abs/2401.04334
Autor:
Tan, Chenjiao, Cao, Qian, Li, Yiwei, Zhang, Jielu, Yang, Xiao, Zhao, Huaqin, Wu, Zihao, Liu, Zhengliang, Yang, Hao, Wu, Nemin, Tang, Tao, Ye, Xinyue, Chai, Lilong, Liu, Ninghao, Li, Changying, Mu, Lan, Liu, Tianming, Mai, Gengchen
The advent of large language models (LLMs) has heightened interest in their potential for multimodal applications that integrate language and vision. This paper explores the capabilities of GPT-4V in the realms of geography, environmental science, ag
Externí odkaz:
http://arxiv.org/abs/2312.17016
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Akademický článek
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