April 2, 2024, 7:52 p.m. | Hongyi Liu, Qingyun Wang, Payam Karisani, Heng Ji

cs.CL updates on arXiv.org arxiv.org

arXiv:2401.10472v2 Announce Type: replace
Abstract: Named entity recognition is a key component of Information Extraction (IE), particularly in scientific domains such as biomedicine and chemistry, where large language models (LLMs), e.g., ChatGPT, fall short. We investigate the applicability of transfer learning for enhancing a named entity recognition model trained in the biomedical domain (the source domain) to be used in the chemical domain (the target domain). A common practice for training such a model in a few-shot learning setting is …

abstract arxiv biomedicine chatgpt chemistry cs.cl domain domains extraction information information extraction key language language models large language large language models life life sciences llms recognition scientific shift transfer transfer learning type via

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