Zobrazeno 1 - 10
of 344
pro vyhledávání: '"Hu Xueyu"'
Autor:
Zhang Zhihao, Ju Cheng, Zuo Xiaoshuang, Ma Yangguang, Wu Tingyu, Yang Yongyong, Yao Zhou, Zhou Jie, Zhang Tao, Hu Xueyu, Wang Zhe
Publikováno v:
Frontiers in Pharmacology, Vol 14 (2023)
Introduction: Osteosarcoma (OS), the primary malignant bone tumor, has a low survival rate for recurrent patients. Latest reports indicated that cancer-associated fibroblasts (CAFs) were the main component of tumor microenvironment, and would generat
Externí odkaz:
https://doaj.org/article/1374490b1a9e456ab823ed83c9008680
Retrieval-Augmented Generation (RAG) has proven to be an effective method for mitigating hallucination issues inherent in large language models (LLMs). Previous approaches typically train retrievers based on semantic similarity, lacking optimization
Externí odkaz:
http://arxiv.org/abs/2411.03957
Structure-based drug design aims at generating high affinity ligands with prior knowledge of 3D target structures. Existing methods either use conditional generative model to learn the distribution of 3D ligands given target binding sites, or iterati
Externí odkaz:
http://arxiv.org/abs/2402.14315
Autor:
Hu, Xueyu, Zhao, Ziyu, Wei, Shuang, Chai, Ziwei, Ma, Qianli, Wang, Guoyin, Wang, Xuwu, Su, Jing, Xu, Jingjing, Zhu, Ming, Cheng, Yao, Yuan, Jianbo, Li, Jiwei, Kuang, Kun, Yang, Yang, Yang, Hongxia, Wu, Fei
In this paper, we introduce InfiAgent-DABench, the first benchmark specifically designed to evaluate LLM-based agents on data analysis tasks. These tasks require agents to end-to-end solving complex tasks by interacting with an execution environment.
Externí odkaz:
http://arxiv.org/abs/2401.05507
Large language models (LLMs) have made significant progress in code generation tasks, but their performance in tackling programming problems with complex data structures and algorithms remains suboptimal. To address this issue, we propose an in-conte
Externí odkaz:
http://arxiv.org/abs/2401.05319
One Model, Multiple Modalities: A Sparsely Activated Approach for Text, Sound, Image, Video and Code
Autor:
Dai, Yong, Tang, Duyu, Liu, Liangxin, Tan, Minghuan, Zhou, Cong, Wang, Jingquan, Feng, Zhangyin, Zhang, Fan, Hu, Xueyu, Shi, Shuming
People perceive the world with multiple senses (e.g., through hearing sounds, reading words and seeing objects). However, most existing AI systems only process an individual modality. This paper presents an approach that excels at handling multiple m
Externí odkaz:
http://arxiv.org/abs/2205.06126
Autor:
Wang, Xuankang, Zhu, Zhijie, Zhang, Zhihao, Liang, Zhuowen, Li, Kun, Ma, Yangguang, Zhou, Jie, Wu, Tingyu, Wang, Zhe, Hu, Xueyu
Publikováno v:
In Experimental Neurology October 2024 380
Autor:
Wu, Tingyu, Ma, Yangguang, Yang, Yongyong, Zhang, Zhihao, Zhou, Jie, Ju, Cheng, Zuo, Xiaoshuang, Wang, Xuankang, Hu, Xueyu, Wang, Zhe
Publikováno v:
In Photodiagnosis and Photodynamic Therapy December 2024 50
Autor:
Shi, Qianyu, Xu, Jiuhui, Chen, Chenglong, Hu, Xueyu, Wang, Boyang, Zeng, Fanwei, Ren, Tingting, Huang, Yi, Guo, Wei, Tang, Xiaodong, Ji, Tao
Publikováno v:
In Cancer Letters 1 June 2024 591
Publikováno v:
In Separation and Purification Technology 25 May 2024 336