Zobrazeno 1 - 10
of 1 435
pro vyhledávání: '"LI Yiwei"'
Autor:
Kim, Sekeun, Jin, Pengfei, Song, Sifan, Chen, Cheng, Li, Yiwei, Ren, Hui, Li, Xiang, Liu, Tianming, Li, Quanzheng
Foundation models have recently gained significant attention because of their generalizability and adaptability across multiple tasks and data distributions. Although medical foundation models have emerged, solutions for cardiac imaging, especially e
Externí odkaz:
http://arxiv.org/abs/2410.23413
Autor:
Li, Yiwei, Zhao, Huaqin, Jiang, Hanqi, Pan, Yi, Liu, Zhengliang, Wu, Zihao, Shu, Peng, Tian, Jie, Yang, Tianze, Xu, Shaochen, Lyu, Yanjun, Blenk, Parker, Pence, Jacob, Rupram, Jason, Banu, Eliza, Liu, Ninghao, Wang, Linbing, Song, Wenzhan, Zhai, Xiaoming, Song, Kenan, Zhu, Dajiang, Li, Beiwen, Wang, Xianqiao, Liu, Tianming
The rapid advances in Large Language Models (LLMs) have the potential to transform manufacturing industry, offering new opportunities to optimize processes, improve efficiency, and drive innovation. This paper provides a comprehensive exploration of
Externí odkaz:
http://arxiv.org/abs/2410.21418
Autor:
Pan, Yi, Jiang, Hanqi, Chen, Junhao, Li, Yiwei, Zhao, Huaqin, Zhou, Yifan, Shu, Peng, Wu, Zihao, Liu, Zhengliang, Zhu, Dajiang, Li, Xiang, Abate, Yohannes, Liu, Tianming
Neuromorphic computing has emerged as a promising energy-efficient alternative to traditional artificial intelligence, predominantly utilizing spiking neural networks (SNNs) implemented on neuromorphic hardware. Significant advancements have been mad
Externí odkaz:
http://arxiv.org/abs/2410.09674
Autor:
Li, Yiwei, Kim, Sekeun, Wu, Zihao, Jiang, Hanqi, Pan, Yi, Jin, Pengfei, Song, Sifan, Shi, Yucheng, Liu, Tianming, Li, Quanzheng, Li, Xiang
Echocardiography (ECHO) is essential for cardiac assessments, but its video quality and interpretation heavily relies on manual expertise, leading to inconsistent results from clinical and portable devices. ECHO video generation offers a solution by
Externí odkaz:
http://arxiv.org/abs/2410.03143
Autor:
Li, Yiwei, Shi, Jiayi, Feng, Shaoxiong, Yuan, Peiwen, Wang, Xinglin, Pan, Boyuan, Wang, Heda, Hu, Yao, Li, Kan
Instruction data is crucial for improving the capability of Large Language Models (LLMs) to align with human-level performance. Recent research LIMA demonstrates that alignment is essentially a process where the model adapts instructions' interaction
Externí odkaz:
http://arxiv.org/abs/2409.19680
Autor:
Zhong, Tianyang, Liu, Zhengliang, Pan, Yi, Zhang, Yutong, Zhou, Yifan, Liang, Shizhe, Wu, Zihao, Lyu, Yanjun, Shu, Peng, Yu, Xiaowei, Cao, Chao, Jiang, Hanqi, Chen, Hanxu, Li, Yiwei, Chen, Junhao, Hu, Huawen, Liu, Yihen, Zhao, Huaqin, Xu, Shaochen, Dai, Haixing, Zhao, Lin, Zhang, Ruidong, Zhao, Wei, Yang, Zhenyuan, Chen, Jingyuan, Wang, Peilong, Ruan, Wei, Wang, Hui, Zhao, Huan, Zhang, Jing, Ren, Yiming, Qin, Shihuan, Chen, Tong, Li, Jiaxi, Zidan, Arif Hassan, Jahin, Afrar, Chen, Minheng, Xia, Sichen, Holmes, Jason, Zhuang, Yan, Wang, Jiaqi, Xu, Bochen, Xia, Weiran, Yu, Jichao, Tang, Kaibo, Yang, Yaxuan, Sun, Bolun, Yang, Tao, Lu, Guoyu, Wang, Xianqiao, Chai, Lilong, Li, He, Lu, Jin, Sun, Lichao, Zhang, Xin, Ge, Bao, Hu, Xintao, Zhang, Lian, Zhou, Hua, Zhang, Lu, Zhang, Shu, Liu, Ninghao, Jiang, Bei, Kong, Linglong, Xiang, Zhen, Ren, Yudan, Liu, Jun, Jiang, Xi, Bao, Yu, Zhang, Wei, Li, Xiang, Li, Gang, Liu, Wei, Shen, Dinggang, Sikora, Andrea, Zhai, Xiaoming, Zhu, Dajiang, Liu, Tianming
This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, spanning multiple domains, including computer science, mathematics, natural sciences, medicine, linguist
Externí odkaz:
http://arxiv.org/abs/2409.18486
Autor:
Hu, Huawen, Shi, Enze, Yue, Chenxi, Yang, Shuocun, Wu, Zihao, Li, Yiwei, Zhong, Tianyang, Zhang, Tuo, Liu, Tianming, Zhang, Shu
Human-in-the-loop reinforcement learning integrates human expertise to accelerate agent learning and provide critical guidance and feedback in complex fields. However, many existing approaches focus on single-agent tasks and require continuous human
Externí odkaz:
http://arxiv.org/abs/2409.11741
Autor:
Zhou, Rong, Yuan, Zhengqing, Yan, Zhiling, Sun, Weixiang, Zhang, Kai, Li, Yiwei, Ye, Yanfang, Li, Xiang, He, Lifang, Sun, Lichao
Biomedical image segmentation is crucial for accurately diagnosing and analyzing various diseases. However, Convolutional Neural Networks (CNNs) and Transformers, the most commonly used architectures for this task, struggle to effectively capture lon
Externí odkaz:
http://arxiv.org/abs/2409.11299
Autor:
Lyu, Yanjun, Wu, Zihao, Zhang, Lu, Zhang, Jing, Li, Yiwei, Ruan, Wei, Liu, Zhengliang, Yu, Xiaowei, Cao, Chao, Chen, Tong, Chen, Minheng, Zhuang, Yan, Li, Xiang, Liu, Rongjie, Huang, Chao, Li, Wentao, Liu, Tianming, Zhu, Dajiang
Pre-trained large language models(LLMs) have attracted increasing attention in biomedical domains due to their success in natural language processing. However, the complex traits and heterogeneity of multi-sources genomics data pose significant chall
Externí odkaz:
http://arxiv.org/abs/2409.09825
Large language models have demonstrated remarkable capabilities in natural language processing, yet their application to political discourse analysis remains underexplored. This paper introduces a novel approach to evaluating presidential debate perf
Externí odkaz:
http://arxiv.org/abs/2409.08147