Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Liao, Weibin"'
In the domain of complex reasoning tasks, such as mathematical reasoning, recent advancements have proposed the use of Direct Preference Optimization (DPO) to suppress output of dispreferred responses, thereby enhancing the long-chain reasoning capab
Externí odkaz:
http://arxiv.org/abs/2410.12854
Acquiring reviewers for academic submissions is a challenging recommendation scenario. Recent graph learning-driven models have made remarkable progress in the field of recommendation, but their performance in the academic reviewer recommendation tas
Externí odkaz:
http://arxiv.org/abs/2407.20684
Autor:
Zhu, Yinghao, Gao, Junyi, Wang, Zixiang, Liao, Weibin, Zheng, Xiaochen, Liang, Lifang, Wang, Yasha, Pan, Chengwei, Harrison, Ewen M., Ma, Liantao
The use of Large Language Models (LLMs) in medicine is growing, but their ability to handle both structured Electronic Health Record (EHR) data and unstructured clinical notes is not well-studied. This study benchmarks various models, including GPT-b
Externí odkaz:
http://arxiv.org/abs/2407.18525
UNet and its variants have been widely used in medical image segmentation. However, these models, especially those based on Transformer architectures, pose challenges due to their large number of parameters and computational loads, making them unsuit
Externí odkaz:
http://arxiv.org/abs/2403.05246
Analyzing the health status of patients based on Electronic Health Records (EHR) is a fundamental research problem in medical informatics. The presence of extensive missing values in EHR makes it challenging for deep neural networks to directly model
Externí odkaz:
http://arxiv.org/abs/2401.16796
Autor:
Zhu, Yinghao, Wang, Zixiang, Gao, Junyi, Tong, Yuning, An, Jingkun, Liao, Weibin, Harrison, Ewen M., Ma, Liantao, Pan, Chengwei
The inherent complexity of structured longitudinal Electronic Health Records (EHR) data poses a significant challenge when integrated with Large Language Models (LLMs), which are traditionally tailored for natural language processing. Motivated by th
Externí odkaz:
http://arxiv.org/abs/2402.01713
While pre-training on object detection tasks, such as Common Objects in Contexts (COCO) [1], could significantly boost the performance of cell segmentation, it still consumes on massive fine-annotated cell images [2] with bounding boxes, masks, and c
Externí odkaz:
http://arxiv.org/abs/2310.03981
Autor:
Liao, Weibin, Xiong, Haoyi, Wang, Qingzhong, Mo, Yan, Li, Xuhong, Liu, Yi, Chen, Zeyu, Huang, Siyu, Dou, Dejing
While self-supervised learning (SSL) algorithms have been widely used to pre-train deep models, few efforts [11] have been done to improve representation learning of X-ray image analysis with SSL pre-trained models. In this work, we study a novel sel
Externí odkaz:
http://arxiv.org/abs/2310.02000
Autor:
Liao, Weibin, Shi, Gen, Lv, Yi, Liu, Lixin, Tang, Xihe, Jin, Yongjian, Ning, Zihan, Zhao, Xihai, Li, Xuesong, Chen, Zhensen
Publikováno v:
In Magnetic Resonance Imaging July 2024 110:86-95
Publikováno v:
In Computer Methods and Programs in Biomedicine May 2023 233