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pro vyhledávání: '"Xing, Sixue"'
Autor:
Light, Jonathan, Xing, Sixue, Liu, Yuanzhe, Chen, Weiqin, Cai, Min, Chen, Xiusi, Wang, Guanzhi, Cheng, Wei, Yue, Yisong, Hu, Ziniu
Effective extraction of the world knowledge in LLMs for complex decision-making tasks remains a challenge. We propose a framework PIANIST for decomposing the world model into seven intuitive components conducive to zero-shot LLM generation. Given onl
Externí odkaz:
http://arxiv.org/abs/2411.15998
The advancement of natural language processing (NLP) in biology hinges on models' ability to interpret intricate biomedical literature. Traditional models often struggle with the complex and domain-specific language in this field. In this paper, we p
Externí odkaz:
http://arxiv.org/abs/2408.02600
Clinical trials need to recruit a sufficient number of volunteer patients to demonstrate the statistical power of the treatment (e.g., a new drug) in curing a certain disease. Clinical trial recruitment has a significant impact on trial success. Fore
Externí odkaz:
http://arxiv.org/abs/2407.13115
Large Language Models (LLMs), originally shown to ace various text comprehension tasks have also remarkably been shown to tackle table comprehension tasks without specific training. While previous research has explored LLM capabilities with tabular d
Externí odkaz:
http://arxiv.org/abs/2406.12719
Large Language Models (LLMs) and multi-agent systems have shown impressive capabilities in natural language tasks but face challenges in clinical trial applications, primarily due to limited access to external knowledge. Recognizing the potential of
Externí odkaz:
http://arxiv.org/abs/2404.14777
Autor:
Yue, Ling, Li, Jonathan, Xing, Sixue, Islam, Md Zabirul, Xia, Bolun, Fu, Tianfan, Chen, Jintai
The clinical trial process, a critical phase in drug development, is essential for developing new treatments. The primary goal of interventional clinical trials is to evaluate the safety and efficacy of drug-based treatments for specific diseases. Ho
Externí odkaz:
http://arxiv.org/abs/2404.13235