Abstract
The report provides a systematic review of the evolution of large language models (LLMs), tracing their development from the emergence of generative AI to the forefront of multimodal and world model advancements. It examines the paradigm shifts induced by AI across scientific research,education, and industrial domains, emphasizing data-driven and collaborative approaches that enhance decision-making processes. The study details the research team's latest innovations in the financial sector, including the Fin-R1 model, constructed through reinforcement learning to augment financial reasoning capabilities; the FinEval benchmark, designed for the rigorous assessment of Chinese financial domain knowledge; the VisFinEval benchmark, a scenario-driven multimodal evaluation framework that encompasses a comprehensive understanding of front-, mid-, and back-office financial operations; and the FinGAIA benchmark, tailored to evaluate AI agents within real-world financial contexts. These advancements underscore the transformative potential of LLMs in financial risk management, customer service, and business transformation, while actively facilitating the intelligent upgrading of the financial industry and contributing to the establishment of an efficient and secure financial ecosystem.
About the speaker
Liwen Zhang is a professor jointly appointed by the School of Statistics and Data Science and Dishui Lake Advanced Institute of Finance, Shanghai University of Finance and Economics. He is also the director of the AI Finance Development and Service Center, the director of the Shanghai Financial Intelligence Engineering Technology Research Center, the deputy director of the Key Laboratory of Mathematical Economics of the Ministry of Education, and the vice dean of the Institute of Data Science and Statistics.
