Zobrazeno 1 - 10
of 30 199
pro vyhledávání: '"YANG, Guang"'
Autor:
Gao, Yijian, Marshall, Dominic, Xing, Xiaodan, Ning, Junzhi, Papanastasiou, Giorgos, Yang, Guang, Komorowski, Matthieu
Radiology reporting generative AI holds significant potential to alleviate clinical workloads and streamline medical care. However, achieving high clinical accuracy is challenging, as radiological images often feature subtle lesions and intricate str
Externí odkaz:
http://arxiv.org/abs/2411.10789
The development of large language models (LLMs) has revolutionized automated code generation. However, their high demand of computation resources has hindered a broader deployment and raised environmental concerns. A common strategy for diminishing c
Externí odkaz:
http://arxiv.org/abs/2411.06680
Autor:
Fang, Yingying, Jin, Zihao, Guo, Shaojie, Liu, Jinda, Gao, Yijian, Ning, Junzhi, Yue, Zhiling, Li, Zhi, Walsh, Simon LF, Yang, Guang
Despite significant advancements in report generation methods, a critical limitation remains: the lack of interpretability in the generated text. This paper introduces an innovative approach to enhance the explainability of text generated by report g
Externí odkaz:
http://arxiv.org/abs/2411.05261
Fibrotic Lung Disease (FLD) is a severe condition marked by lung stiffening and scarring, leading to respiratory decline. High-resolution computed tomography (HRCT) is critical for diagnosing and monitoring FLD; however, fibrosis appears as irregular
Externí odkaz:
http://arxiv.org/abs/2411.03551
Autor:
Burgarella, Denis, Buat, Véronique, Theulé, Patrice, Zavala, Jorge, Haro, Pablo Arrabal, Bagley, Micaela B., Boquien, Médéric, Cleri, Nikko, Dewachter, Tim, Dickinson, Mark, Ferguson, Henry C., Fernández, Vital, Finkelstein, Steven L., Fontana, Adriano, Gawiser, Eric, Grazian, Andrea, Grogin, Norman, Holwerda, Benne W., Kartaltepe, Jeyhan S., Kewley, Lisa, Kirkpatrick, Allison, Kocevski, Dale, Koekemoer, Anton M., Long, Arianna, Lotz, Jennifer, Lucas, Ray A., Mobasher, Bahram, Papovich, Casey, Pérez-González, Pablo G., Pirzkal, Nor, Ravindranath, Swara, Rodighiero, Giulia, Roehlly, Yannick, Rose, Caitlin, Seillé, Lise-Marie, Somerville, Rachel, Wilkins, Steve, Yang, Guang, Yung, L. Y. Aaron
We investigate the coevolution of metals and dust for 173 galaxies at 4.0
Externí odkaz:
http://arxiv.org/abs/2410.23959
Autor:
Yang, Guang, Zhou, Yu, Cheng, Wei, Zhang, Xiangyu, Chen, Xiang, Zhuo, Terry Yue, Liu, Ke, Zhou, Xin, Lo, David, Chen, Taolue
The widespread use of Large Language Models (LLMs) in software engineering has intensified the need for improved model and resource efficiency. In particular, for neural code generation, LLMs are used to translate function/method signature and DocStr
Externí odkaz:
http://arxiv.org/abs/2410.22793
Deep generative models have significantly advanced medical imaging analysis by enhancing dataset size and quality. Beyond mere data augmentation, our research in this paper highlights an additional, significant capacity of deep generative models: the
Externí odkaz:
http://arxiv.org/abs/2410.13823
Modern physics simulation often involves multiple functions of interests, and traditional numerical approaches are known to be complex and computationally costly. While machine learning-based surrogate models can offer significant cost reductions, mo
Externí odkaz:
http://arxiv.org/abs/2410.13794
Autor:
Cai, Wenlong, Chen, Zanhong, Shi, Yuzhang, Zhu, Daoqian, Yang, Guang, Du, Ao, Lu, Shiyang, Cao, Kaihua, Liu, Hongxi, Shi, Kewen, Zhao, Weisheng
Current-induced antiferromagnetic (AFM) switching remains critical in spintronics, yet the interplay between thermal effects and spin torques still lacks clear clarification. Here we experimentally investigate the thermally interplayed spin-orbit tor
Externí odkaz:
http://arxiv.org/abs/2410.13202
Domain adaptation, which bridges the distributions across different modalities, plays a crucial role in multimodal medical image analysis. In endoscopic imaging, combining pre-operative data with intra-operative imaging is important for surgical plan
Externí odkaz:
http://arxiv.org/abs/2410.13896