Zobrazeno 1 - 10
of 104 133
pro vyhledávání: '"and, Leong"'
Generalizable Neural Radiance Field (GNeRF) across scenes has been proven to be an effective way to avoid per-scene optimization by representing a scene with deep image features of source images. However, despite its potential for real-world applicat
Externí odkaz:
http://arxiv.org/abs/2411.11691
Autor:
Zhan, Yuancheng, Zhang, Hui, Erbanni, Rebecca, Burger, Andreas, Wan, Lingxiao, Jiang, Xudong, Chae, Sanghoon, Liu, Aiqun, Poletti, Dario, Kwek, Leong Chuan
Quantum evolution is crucial for the understanding of complex quantum systems. However, current implementations of time evolution on quantum photonic platforms face challenges of limited light source efficiency due to propagation loss and merely sing
Externí odkaz:
http://arxiv.org/abs/2411.11307
This paper explores the transformative role of artificial intelligence (AI) in enhancing scientific research, particularly in the fields of brain science and social sciences. We analyze the fundamental aspects of human research and argue that it is h
Externí odkaz:
http://arxiv.org/abs/2411.12761
Autor:
Liu, Zichen, Yu, Yue, Ouyang, Hao, Wang, Qiuyu, Cheng, Ka Leong, Wang, Wen, Liu, Zhiheng, Chen, Qifeng, Shen, Yujun
Image editing involves a variety of complex tasks and requires efficient and precise manipulation techniques. In this paper, we present MagicQuill, an integrated image editing system that enables swift actualization of creative ideas. Our system feat
Externí odkaz:
http://arxiv.org/abs/2411.09703
Autor:
Yin, Qingyu, Leong, Chak Tou, Zhang, Hongbo, Zhu, Minjun, Yan, Hanqi, Zhang, Qiang, He, Yulan, Li, Wenjie, Wang, Jun, Zhang, Yue, Yang, Linyi
The alignment of large language models (LLMs) with human preferences remains a key challenge. While post-training techniques like Reinforcement Learning from Human Feedback (RLHF) and Direct Preference Optimization (DPO) have achieved notable success
Externí odkaz:
http://arxiv.org/abs/2411.07618
Autor:
Zhu, Yongda, Bakx, Tom J. L. C., Ikeda, Ryota, Umehata, Hideki, Becker, George D., Cain, Christopher, Champagne, Jaclyn B., Fan, Xiaohui, Fudamoto, Yoshinobu, Jin, Xiangyu, Ma, Hai-Xia, Sun, Yang, Takeuchi, Tsutomu T., Tee, Wei Leong
We report the discovery of a unique quasar-dusty star-forming galaxy (DSFG) system at $z = 5.63$, consisting of the bright quasar J1133+1603 ($M_{\rm UV} = -27.42$) and its compact, dust-obscured companion, J1133c. ALMA observations reveal a prominen
Externí odkaz:
http://arxiv.org/abs/2411.06698
This paper presents an innovative pseudo-haptic model for weight simulation in virtual reality (VR) environments. By integrating visual feedback with voluntary exerted force through a passive haptic glove, the model creates haptic illusions of weight
Externí odkaz:
http://arxiv.org/abs/2411.05133
Electronic maps consist of diverse entities, such as points of interest (POIs), road networks, and land parcels, playing a vital role in applications like ITS and LBS. Map entity representation learning (MapRL) generates versatile and reusable data r
Externí odkaz:
http://arxiv.org/abs/2411.00874
Deep Reinforcement Learning (DRL) has achieved remarkable success in solving complex decision-making problems by combining the representation capabilities of deep learning with the decision-making power of reinforcement learning. However, learning in
Externí odkaz:
http://arxiv.org/abs/2410.20487
Autor:
Xu, Kaishuai, Yu, Tiezheng, Hou, Wenjun, Cheng, Yi, Leong, Chak Tou, Li, Liangyou, Jiang, Xin, Shang, Lifeng, Liu, Qun, Li, Wenjie
Large Language Models (LLMs) have exhibited strong mathematical reasoning and computational prowess, tackling tasks ranging from basic arithmetic to advanced competition-level problems. However, frequently occurring subtle errors, such as miscalculat
Externí odkaz:
http://arxiv.org/abs/2410.06638