库帕思高质量金融全科思维链（Chain-of-Thought）数据集

本数据集面向教育大模型研发团队、金融科技企业及金融机构，旨在解决金融领域多学科知识体系复杂、跨领域推理能力不足等痛点。通过系统化清洗和思维链重构，整合了银行业务、证券投资、保险精算、基金理财、期货衍生品、税务筹划、财务会计、风险管理、理财规划等十大核心金融领域的试题资源，涵盖从基础金融知识到高级专业实务的全方位内容。

通过思维链训练，可为基座大模型提供金融全领域的通识能力培养，同时助力金融垂类模型在跨领域业务场景下的专业推理能力提升。与单一领域数据集不同，本数据集特别设计了跨科目复合题型的思维链标注。

This dataset is targeted at educational large language model (LLM) R&D teams, fintech enterprises and financial institutions, aiming to address the pain points in the financial sector such as the complexity of multi-disciplinary knowledge systems and insufficient cross-domain reasoning capabilities.

Through systematic cleaning and chain-of-thought reconstruction, it integrates question bank resources from ten core financial fields including banking business, securities investment, insurance actuarial science, fund wealth management, futures and derivatives, tax planning, financial accounting, risk management and financial planning, covering comprehensive content ranging from basic financial knowledge to advanced professional practices.

Through chain-of-thought training, it can equip base large language models with general literacy capabilities across the entire financial domain, and also help financial vertical models enhance their professional reasoning capabilities in cross-domain business scenarios.

Unlike single-domain datasets, this dataset specially designs chain-of-thought annotations for cross-subject composite question types.

搜集汇总

背景与挑战

背景概述

该数据集面向教育大模型研发和金融科技领域，旨在通过整合十大核心金融领域的试题资源，解决金融多学科知识复杂和跨领域推理不足的问题。它采用思维链训练，帮助大模型提升金融通识和跨领域专业推理能力，并特别设计了跨科目复合题型的标注。