With the rise of generative AI, the prompt trading market is rapidly expanding. However, current trading platforms, exemplified by PromptBase, are predominantly seller-driven in pricing and lack objective price measurement standards. In response to this challenge, the multimedia and intelligent security team at Fudan University has proposed an innovative prompt trading model aimed at better adapting to a future buyer-driven market. This new trading model consists of two main phases: prompt category selection and pricing strategy formulation. In the first phase, the platform employs a greedy search-based multi-armed bandit algorithm to...

A research team from Fudan University has developed the 'Concept Erasure Technique' (RECE), which can efficiently and accurately modify inappropriate ideas in AI models, significantly reducing the likelihood of generating inappropriate images while maintaining the AI's other creative capabilities. This technology uses a 'closed solution' to locate and modify specific parts, ensuring the AI behaves more appropriately during creation and stays on track. Experiments show that the RECE technology can effectively enhance the morality and quality of AI creations, providing new directions for the future development of AI, making future AI assistants smarter and more perceptive.

In the field of 3D digital humans, research teams from Nanjing University, Fudan University, and Huawei Noah's Ark Lab have proposed innovative solutions to address the issues of multi-view consistency and insufficient emotional expressiveness. They developed the EmoTalk3D dataset, which includes calibrated multi-view videos, emotion annotations, and frame-by-frame 3D geometric information. By constructing a mapping framework from 'speech to geometry to appearance', the research team introduced a new method that enables the synthesis of 3D talking avatars with controllable emotions, significantly enhancing lip synchronization and rendering quality.

Fudan University Affiliated Zhongshan Hospital and Guangqi Huiyu have jointly released the Guangyu Medical Large Model, deeply participating in the customization of medical AI capability models that can be applied to various medical scenarios such as disease diagnosis and doctor-patient communication. The model's professionalism and credibility are ensured through high-quality medical training corpus. The Guangyu Medical Large Model, based on hundreds of billions of parameters and high-quality medical knowledge data, aims to improve the quality and efficiency of medical services and promote the comprehensive application of medical AI.