Feb. 22, 2024, 5:42 a.m. | Hengchuang Yin, Zhonghui Gu, Fanhao Wang, Yiparemu Abuduhaibaier, Yanqiao Zhu, Xinming Tu, Xian-Sheng Hua, Xiao Luo, Yizhou Sun

cs.LG updates on arXiv.org arxiv.org

arXiv:2402.13714v1 Announce Type: cross
Abstract: Large language models (LLMs) such as ChatGPT have gained considerable interest across diverse research communities. Their notable ability for text completion and generation has inaugurated a novel paradigm for language-interfaced problem solving. However, the potential and efficacy of these models in bioinformatics remain incompletely explored. In this work, we study the performance LLMs on a wide spectrum of crucial bioinformatics tasks. These tasks include the identification of potential coding regions, extraction of named entities for …

abstract arxiv bioinformatics chatgpt communities cs.ai cs.lg diverse evaluation language language models large language large language models llms novel paradigm q-bio.qm research text type

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