Group 1 - The core viewpoint of the news is the launch of the CUFEL financial model and the CUFEL-A research report intelligent agent by a team from the Central University of Finance and Economics, marking a significant step in promoting independent innovation in financial technology [1] - The CUFEL model features a high-efficiency model fine-tuning process that enhances performance in vertical fields while maintaining general capabilities, providing substantial value in industry applications, particularly in intelligent agent construction and local deployment [1] - The CUFEL-A intelligent agent generates research reports on A-share listed companies through a four-step process: data aggregation, planning, structuring and reflection, and writing, utilizing a report evaluation algorithm based on tens of thousands of brokerage reports to improve report quality [1] Group 2 - The team is actively collaborating with leading companies in the financial industry to explore applications in areas such as intelligent credit, compliance, and supply chain finance [2] - The 2025 Zhongguancun Forum series, themed "China and the World Economy in the Era of Digital Intelligence," aims to interpret the logic of China's economic development and contribute to a new paradigm of global financial governance [2] - The Central University of Finance and Economics emphasizes talent cultivation as a foundational project for the digital intelligence era, aiming to develop compound talents with digital literacy and global vision [2]

Group 1 - The CUFEL model and the CUFEL-A research report generation agent were officially launched at the Global Finance Forum hosted by Central University of Finance and Economics on July 5 [1] - CUFEL is described as not just a single model but a cluster of models or an efficient model fine-tuning process, enhancing performance in specific tasks while maintaining general capabilities [3] - The CUFEL-A agent produces independent and in-depth research reports on A-share listed companies through a four-step process: data aggregation, planning, structuring and reflection, and writing [5] Group 2 - The research report evaluation algorithm is built on three principles: generative, end-to-end, and multi-agent system reinforcement learning, improving the quality of report writing [5] - The model was developed by a team of faculty and students from the Central University of Finance and Economics, which is actively collaborating with leading companies in the financial industry to explore applications in smart credit, compliance, and supply chain finance [5]