Zobrazeno 1 - 10
of 23 981
pro vyhledávání: '"Wee, P."'
Autor:
Lee, Jungho, Cho, Suhwan, Kim, Taeoh, Jang, Ho-Deok, Lee, Minhyeok, Cha, Geonho, Wee, Dongyoon, Lee, Dogyoon, Lee, Sangyoun
3D Gaussian Splatting (3DGS) has attracted significant attention for its high-quality novel view rendering, inspiring research to address real-world challenges. While conventional methods depend on sharp images for accurate scene reconstruction, real
Externí odkaz:
http://arxiv.org/abs/2412.16028
With the rapid advancement of artificial intelligence and deep learning, medical image analysis has become a critical tool in modern healthcare, significantly improving diagnostic accuracy and efficiency. However, AI-based methods also raise serious
Externí odkaz:
http://arxiv.org/abs/2412.03924
We introduce, for the first time, a cohomology-based Gromov-Hausdorff ultrametric method to analyze 1-dimensional and higher-dimensional (co)homology groups, focusing on loops, voids, and higher-dimensional cavity structures in simplicial complexes,
Externí odkaz:
http://arxiv.org/abs/2411.13887
Autor:
Lim, Wee Han, Tanttu, Tuomo, Youn, Tony, Huang, Jonathan Yue, Serrano, Santiago, Dickie, Alexandra, Yianni, Steve, Hudson, Fay E., Escott, Christopher C., Yang, Chih Hwan, Laucht, Arne, Saraiva, Andre, Chan, Kok Wai, Cifuentes, Jesús D., Dzurak, Andrew S.
Recent advances in semiconductor spin qubits have achieved linear arrays exceeding ten qubits. Moving to two-dimensional (2D) qubit arrays is a critical next step to advance towards fault-tolerant implementations, but it poses substantial fabrication
Externí odkaz:
http://arxiv.org/abs/2411.13882
Autor:
Jia, Xiaojun, Huang, Yihao, Liu, Yang, Tan, Peng Yan, Yau, Weng Kuan, Mak, Mun-Thye, Sim, Xin Ming, Ng, Wee Siong, Ng, See Kiong, Liu, Hanqing, Zhou, Lifeng, Yan, Huanqian, Sun, Xiaobing, Liu, Wei, Wang, Long, Qian, Yiming, Liu, Yong, Yang, Junxiao, Zhang, Zhexin, Lei, Leqi, Chen, Renmiao, Lu, Yida, Cui, Shiyao, Wang, Zizhou, Li, Shaohua, Wang, Yan, Goh, Rick Siow Mong, Zhen, Liangli, Zhang, Yingjie, Zhao, Zhe
This paper introduces the Global Challenge for Safe and Secure Large Language Models (LLMs), a pioneering initiative organized by AI Singapore (AISG) and the CyberSG R&D Programme Office (CRPO) to foster the development of advanced defense mechanisms
Externí odkaz:
http://arxiv.org/abs/2411.14502
Autor:
Wee, JunJie, Wei, Guo-Wei
The fast evolution of SARS-CoV-2 and other infectious viruses poses a grand challenge to the rapid response in terms of viral tracking, diagnostics, and design and manufacture of monoclonal antibodies (mAbs) and vaccines, which are both time-consumin
Externí odkaz:
http://arxiv.org/abs/2411.12370
Conversational Recommender Systems (CRSs) aim to provide personalized recommendations through dynamically capturing user preferences in interactive conversations. Conventional CRSs often extract user preferences as hidden representations, which are c
Externí odkaz:
http://arxiv.org/abs/2411.14459
Autor:
Zhao, Kai, Li, Xuhao, Kang, Qiyu, Ji, Feng, Ding, Qinxu, Zhao, Yanan, Liang, Wenfei, Tay, Wee Peng
We introduce the Distributed-order fRActional Graph Operating Network (DRAGON), a novel continuous Graph Neural Network (GNN) framework that incorporates distributed-order fractional calculus. Unlike traditional continuous GNNs that utilize integer-o
Externí odkaz:
http://arxiv.org/abs/2411.05274
We study methods for efficiently aligning large language models (LLMs) with human preferences given budgeted online feedback. We first formulate the LLM alignment problem in the frame of contextual dueling bandits. This formulation, subsuming recent
Externí odkaz:
http://arxiv.org/abs/2411.01493
Autor:
Wee, Phil, Baghdadi, Riyadh
Recently, there has been an explosion of large language models created through fine-tuning with data from larger models. These small models able to produce outputs that appear qualitatively similar to significantly larger models. However, one of the
Externí odkaz:
http://arxiv.org/abs/2411.00878