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ChemVLM: Exploring the Power of Multimodal Large Language Models in Chemistry Area

Autor: Li, Junxian, Zhang, Di, Wang, Xunzhi, Hao, Zeying, Lei, Jingdi, Tan, Qian, Zhou, Cai, Liu, Wei, Yang, Yaotian, Xiong, Xinrui, Wang, Weiyun, Chen, Zhe, Wang, Wenhai, Li, Wei, Zhang, Shufei, Su, Mao, Ouyang, Wanli, Li, Yuqiang, Zhou, Dongzhan

Large Language Models (LLMs) have achieved remarkable success and have been applied across various scientific fields, including chemistry. However, many chemical tasks require the processing of visual information, which cannot be successfully handled

Externí odkaz: http://arxiv.org/abs/2408.07246

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Unveiling the Lexical Sensitivity of LLMs: Combinatorial Optimization for Prompt Enhancement

Autor: Zhan, Pengwei, Xu, Zhen, Tan, Qian, Song, Jie, Xie, Ru

Large language models (LLMs) demonstrate exceptional instruct-following ability to complete various downstream tasks. Although this impressive ability makes LLMs flexible task solvers, their performance in solving tasks also heavily relies on instruc

Externí odkaz: http://arxiv.org/abs/2405.20701

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Akademický článek

Machine Learning–Driven Models to Predict Prognostic Outcomes in Patients Hospitalized With Heart Failure Using Electronic Health Records: Retrospective Study

Autor: Lv, Haichen, Yang, Xiaolei, Wang, Bingyi, Wang, Shaobo, Du, Xiaoyan, Tan, Qian, Hao, Zhujing, Liu, Ying, Yan, Jun, Xia, Yunlong

Publikováno v: Journal of Medical Internet Research, Vol 23, Iss 4, p e24996 (2021)

BackgroundWith the prevalence of cardiovascular diseases increasing worldwide, early prediction and accurate assessment of heart failure (HF) risk are crucial to meet the clinical demand. ObjectiveOur study objective was to develop machine learning

Externí odkaz: https://doaj.org/article/0816f26dde764ef09d5b7b3d2c7e2b25

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ChemLLM: A Chemical Large Language Model

Autor: Zhang, Di, Liu, Wei, Tan, Qian, Chen, Jingdan, Yan, Hang, Yan, Yuliang, Li, Jiatong, Huang, Weiran, Yue, Xiangyu, Ouyang, Wanli, Zhou, Dongzhan, Zhang, Shufei, Su, Mao, Zhong, Han-Sen, Li, Yuqiang

Large language models (LLMs) have made impressive progress in chemistry applications. However, the community lacks an LLM specifically designed for chemistry. The main challenges are two-fold: firstly, most chemical data and scientific knowledge are

Externí odkaz: http://arxiv.org/abs/2402.06852

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