Zobrazeno 1 - 10
of 9 902
pro vyhledávání: '"SHU, Wei"'
Autor:
Ke, Yu He, Jin, Liyuan, Elangovan, Kabilan, Ong, Bryan Wen Xi, Oh, Chin Yang, Sim, Jacqueline, Loh, Kenny Wei-Tsen, Soh, Chai Rick, Cheng, Jonathan Ming Hua, Lee, Aaron Kwang Yang, Ting, Daniel Shu Wei, Liu, Nan, Abdullah, Hairil Rizal
Large Language Models (LLMs) are emerging as powerful tools in healthcare, particularly for complex, domain-specific tasks. This study describes the development and evaluation of the PErioperative AI CHatbot (PEACH), a secure LLM-based system integra
Externí odkaz:
http://arxiv.org/abs/2412.18096
The electron spectrum exhibits a complex structure and has controversially proposed origins. This work reproduce the evolution of the electron spectrum based on a spatially dependent propagation (SDP) model. The key point is that our SPD model featur
Externí odkaz:
http://arxiv.org/abs/2412.09016
The high computational, memory, and energy demands of Deep Learning (DL) applications often exceed the capabilities of battery-powered edge devices, creating difficulties in meeting task deadlines and accuracy requirements. Unlike previous solutions
Externí odkaz:
http://arxiv.org/abs/2411.19487
Autor:
Ke, Yu He, Jin, Liyuan, Elangovan, Kabilan, Abdullah, Hairil Rizal, Liu, Nan, Sia, Alex Tiong Heng, Soh, Chai Rick, Tung, Joshua Yi Min, Ong, Jasmine Chiat Ling, Kuo, Chang-Fu, Wu, Shao-Chun, Kovacheva, Vesela P., Ting, Daniel Shu Wei
Large Language Models (LLMs) show potential for medical applications but often lack specialized clinical knowledge. Retrieval Augmented Generation (RAG) allows customization with domain-specific information, making it suitable for healthcare. This st
Externí odkaz:
http://arxiv.org/abs/2410.08431
Large vision language models (VLMs) combine large language models with vision encoders, demonstrating promise across various tasks. However, they often underperform in task-specific applications due to domain gaps between pre-training and fine-tuning
Externí odkaz:
http://arxiv.org/abs/2410.06456
Autor:
Musgrave, Jonathan, Huang, Shu-Wei
Ultrafast optics is driven by a myriad of complex nonlinear dynamics. The ubiquitous presence of governing equations in the form of partial integro-differential equations (PIDE) necessitates the need for advanced computational tools to understand the
Externí odkaz:
http://arxiv.org/abs/2409.19895
We study behavior change-based visual risk object identification (Visual-ROI), a critical framework designed to detect potential hazards for intelligent driving systems. Existing methods often show significant limitations in spatial accuracy and temp
Externí odkaz:
http://arxiv.org/abs/2409.15846
Autor:
Chen, Zheng-Zhe, Lin, Hsiang-Ting, Chang, Chiao-Yun, Muhammad, Adil, Tsai, Po-Cheng, Kao, Tsung Sheng, Chen, Chi, Chang, Shu-Wei, Lin, Shih-Yen, Shih, Min-Hsiung
Two-dimensional (2-D) monolayer transition-metal dichalcogenides (TMDCs) are promising materials for realizing ultracompact, low-threshold semiconductor lasers. And the development of the electrical-driven TMDC devices is crucial for enhancing the in
Externí odkaz:
http://arxiv.org/abs/2408.06979
Autor:
Elangovan, Kabilan, Ong, Jasmine Chiat Ling, Jin, Liyuan, Seng, Benjamin Jun Jie, Kwan, Yu Heng, Tan, Lit Soo, Zhong, Ryan Jian, Ma, Justina Koi Li, Ke, YuHe, Liu, Nan, Giacomini, Kathleen M, Ting, Daniel Shu Wei
Large Language Models (LLMs) have emerged as a potential solution to assist digital health development with patient education, commonly medication-related enquires. We trained and validated Med-Pal, a medication domain-specific LLM-chatbot fine-tuned
Externí odkaz:
http://arxiv.org/abs/2407.12822
Autor:
Yang, Rui, Ning, Yilin, Keppo, Emilia, Liu, Mingxuan, Hong, Chuan, Bitterman, Danielle S, Ong, Jasmine Chiat Ling, Ting, Daniel Shu Wei, Liu, Nan
Generative artificial intelligence (AI) has brought revolutionary innovations in various fields, including medicine. However, it also exhibits limitations. In response, retrieval-augmented generation (RAG) provides a potential solution, enabling mode
Externí odkaz:
http://arxiv.org/abs/2406.12449