Zobrazeno 1 - 10
of 3 874
pro vyhledávání: '"Wen, Chuan"'
Autor:
Yu, Han-Cheng, Shih, Yu-An, Law, Kin-Man, Hsieh, Kai-Yu, Cheng, Yu-Chen, Ho, Hsin-Chih, Lin, Zih-An, Hsu, Wen-Chuan, Fan, Yao-Chung
In this paper, we tackle the task of distractor generation (DG) for multiple-choice questions. Our study introduces two key designs. First, we propose \textit{retrieval augmented pretraining}, which involves refining the language model pretraining to
Externí odkaz:
http://arxiv.org/abs/2406.13578
Spatial relationships between objects represent key scene information for humans to understand and interact with the world. To study the capability of current computer vision systems to recognize physically grounded spatial relations, we start by pro
Externí odkaz:
http://arxiv.org/abs/2403.00729
Autor:
Yang, Yi-Chen, Cho, Soohyun, Li, Tong-Rui, Liu, Xiang-Qi, Liu, Zheng-Tai, Jiang, Zhi-Cheng, Ding, Jian-Yang, Xia, Wei, Tao, Zi-Cheng, Liu, Jia-Yu, Jing, Wen-Chuan, Huang, Yu, Shi, Yu-Ming, Huh, Soonsang, Kondo, Takeshi, Sun, Zhe, Liu, Ji-Shan, Ye, Mao, Wang, Yi-Lin, Guo, Yan-Feng, Shen, Da-Wei
The charge density wave (CDW), as a hallmark of vanadium-based kagome superconductor AV3Sb5 (A = K, Rb, Cs), has attracted intensive attention. However, the fundamental controversy regarding the underlying mechanism of CDW therein persists. Recently,
Externí odkaz:
http://arxiv.org/abs/2402.03765
Quantum secret sharing (QSS) is the result of merging the principles of quantum mechanics with secret information sharing. It enables a sender to share a secret among receivers, and the receivers can then collectively recover the secret when the need
Externí odkaz:
http://arxiv.org/abs/2402.02413
We address the challenge of acquiring real-world manipulation skills with a scalable framework.Inspired by the success of large-scale auto-regressive prediction in Large Language Models (LLMs), we hold the belief that identifying an appropriate predi
Externí odkaz:
http://arxiv.org/abs/2401.11439
Learning from demonstration is a powerful method for teaching robots new skills, and having more demonstration data often improves policy learning. However, the high cost of collecting demonstration data is a significant bottleneck. Videos, as a rich
Externí odkaz:
http://arxiv.org/abs/2401.00025
Autor:
Liu, Yuyang, Dong, Weijun, Hu, Yingdong, Wen, Chuan, Yin, Zhao-Heng, Zhang, Chongjie, Gao, Yang
Humans often acquire new skills through observation and imitation. For robotic agents, learning from the plethora of unlabeled video demonstration data available on the Internet necessitates imitating the expert without access to its action, presenti
Externí odkaz:
http://arxiv.org/abs/2310.07433
Autor:
Ya-Chi Yang, Yueh Chien, Aliaksandr A. Yarmishyn, Lee-Yieng Lim, Hao-Yu Tsai, Wen-Chuan Kuo, Ping-Hsing Tsai, Sheng-Hsien Yang, Shao-I Hong, Shih-Jen Chen, De-Kuang Hwang, Yi-Ping Yang, Shih-Hwa Chiou
Publikováno v:
Journal of Advanced Research, Vol 60, Iss , Pp 141-157 (2024)
Introduction: Epithelial-mesenchymal transition (EMT) of retinal pigment epithelial (RPE) cells is related to the pathogenesis of various retinopathies including age-related macular degeneration (AMD). Oxidative stress is the major factor that induce
Externí odkaz:
https://doaj.org/article/d9aaf9dcd9f142e5bfe08fefa6711385
Imagining the future trajectory is the key for robots to make sound planning and successfully reach their goals. Therefore, text-conditioned video prediction (TVP) is an essential task to facilitate general robot policy learning. To tackle this task
Externí odkaz:
http://arxiv.org/abs/2303.14897