Zobrazeno 1 - 10
of 2 046
pro vyhledávání: '"LI, YIWEI"'
Autor:
Chen, Junhao, Shu, Peng, Li, Yiwei, Zhao, Huaqin, Jiang, Hanqi, Pan, Yi, Zhou, Yifan, Liu, Zhengliang, Howe, Lewis C, Liu, Tianming
Recent studies show that large language models (LLMs) are powerful tools for working with natural language, bringing advances in many areas of computational linguistics. However, these models face challenges when applied to low-resource languages due
Externí odkaz:
http://arxiv.org/abs/2412.05184
Autor:
Zhong, Tianyang, Yang, Zhenyuan, Liu, Zhengliang, Zhang, Ruidong, Liu, Yiheng, Sun, Haiyang, Pan, Yi, Li, Yiwei, Zhou, Yifan, Jiang, Hanqi, Chen, Junhao, Liu, Tianming
Low-resource languages serve as invaluable repositories of human history, embodying cultural evolution and intellectual diversity. Despite their significance, these languages face critical challenges, including data scarcity and technological limitat
Externí odkaz:
http://arxiv.org/abs/2412.04497
Autor:
Jiang, Hanqi, Pan, Yi, Chen, Junhao, Liu, Zhengliang, Zhou, Yifan, Shu, Peng, Li, Yiwei, Zhao, Huaqin, Mihm, Stephen, Howe, Lewis C, Liu, Tianming
Oracle bone script (OBS), as China's earliest mature writing system, present significant challenges in automatic recognition due to their complex pictographic structures and divergence from modern Chinese characters. We introduce OracleSage, a novel
Externí odkaz:
http://arxiv.org/abs/2411.17837
Autor:
Shu, Peng, Chen, Junhao, Liu, Zhengliang, Wang, Hui, Wu, Zihao, Zhong, Tianyang, Li, Yiwei, Zhao, Huaqin, Jiang, Hanqi, Pan, Yi, Zhou, Yifan, Owl, Constance, Zhai, Xiaoming, Liu, Ninghao, Saunt, Claudio, Liu, Tianming
Large Language Models (LLMs) have demonstrated remarkable success across a wide range of tasks and domains. However, their performance in low-resource language translation, particularly when translating into these languages, remains underexplored. Th
Externí odkaz:
http://arxiv.org/abs/2411.11295
Autor:
Xu, Shaochen, Zhou, Yifan, Liu, Zhengliang, Wu, Zihao, Zhong, Tianyang, Zhao, Huaqin, Li, Yiwei, Jiang, Hanqi, Pan, Yi, Chen, Junhao, Lu, Jin, Zhang, Wei, Zhang, Tuo, Zhang, Lu, Zhu, Dajiang, Li, Xiang, Liu, Wei, Li, Quanzheng, Sikora, Andrea, Zhai, Xiaoming, Xiang, Zhen, Liu, Tianming
Artificial Intelligence (AI) has become essential in modern healthcare, with large language models (LLMs) offering promising advances in clinical decision-making. Traditional model-based approaches, including those leveraging in-context demonstration
Externí odkaz:
http://arxiv.org/abs/2411.14461
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:
Yang, Zhenyuan, Liu, Zhengliang, Zhang, Jing, Lu, Cen, Tai, Jiaxin, Zhong, Tianyang, Li, Yiwei, Zhao, Siyan, Yao, Teng, Liu, Qing, Yang, Jinlin, Liu, Qixin, Li, Zhaowei, Wang, Kexin, Ma, Longjun, Zhu, Dajiang, Ren, Yudan, Ge, Bao, Zhang, Wei, Qiang, Ning, Zhang, Tuo, Liu, Tianming
This study examines the capabilities of advanced Large Language Models (LLMs), particularly the o1 model, in the context of literary analysis. The outputs of these models are compared directly to those produced by graduate-level human participants. B
Externí odkaz:
http://arxiv.org/abs/2410.18142
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