大数据2025，Vol.11Issue(2)：3-18,16.DOI:10.11959/j.issn.2096-0271.2025021
知识增强的中文金融大模型研究
Research on knowledge-augmented Chinese financial large language model
摘要
Abstract
The financial industry has long faced challenges in processing vast amounts of market data and information.Currently,large language models have made significant progress in general text understanding tasks,but there is still considerable room for improvement in more specialized domains,such as Chinese finance.To address the limitations of current large language models in handling professional domain-specific text tasks,a two-stage training approach based on finance knowledge-enhanced continued pre-training and supervised fine-tuning is designed.This approach improves the organization of training data and the training paradigm,thereby enhancing the model's capabilities in complex financial scenarios.Finally,experiments have validated the effectiveness of the proposed knowledge-enhanced approach in large model training.关键词
知识增强/大语言模型/金融时序预测Key words
knowledge augmentation/large language model/financial time series forecasting分类
计算机与自动化引用本文复制引用
程大伟,贾仁军,李江彤,丁志军,蒋昌俊..知识增强的中文金融大模型研究[J].大数据,2025,11(2):3-18,16.基金项目
国家重点研发计划项目(No.2022YFB4501704) （No.2022YFB4501704）
国家自然科学基金项目(No.62102287,No.62472317) （No.62102287,No.62472317）
上海市科技创新行动计划项目(No.22YS1400600,No.24692118300) The National Key R&D Program of China(No.2022YFB4501704),The National Natural Science Foundation of China(No.62102287,No.62472317),Shanghai Science and Technology Innovation Action Plan Project(No.22YS1400600,No.24692118300) （No.22YS1400600,No.24692118300）
