June 7, 2024, 4:51 a.m. | Chun-Hsien Lin, Pu-Jen Cheng

cs.CL updates on arXiv.org arxiv.org

arXiv:2406.04202v1 Announce Type: new
Abstract: With the development of large-scale Language Models (LLM), fine-tuning pre-trained LLM has become a mainstream paradigm for solving downstream tasks of natural language processing. However, training a language model in the legal field requires a large number of legal documents so that the language model can learn legal terminology and the particularity of the format of legal documents. The typical NLP approaches usually rely on many manually annotated data sets for training. However, in the …

abstract arxiv become cs.ai cs.cl development documents fine-tuning however language language model language models language processing large language large language model legal llm natural natural language natural language processing paradigm processing scale tasks training type

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