Tongji, Fudan University jointly release RAG technology to solve large model illusion problem

existartificial intelligence (AI)Fields.large modelhas become a cornerstone of many applications. However, with the wide range of applications, the problem of the illusion of large models has become more and more prominent. Recently, a team of researchers from Tongji University and Fudan University have teamed up to release a new method called "Retrieval Augmented Generation (RAG)", which aims to solve this challenge.

The core idea of RAG is to retrieve relevant information from an external knowledge base before answering a question in order to enhance the accuracy of the answer and reduce the model's illusions. This approach is particularly suitable for knowledge-intensive tasks where, by citing sources, users can verify the accuracy of the answer and increase trust in the model's output.

The publication of this research certainly provides new ideas for solving the problem of large model hallucinations.RAG not only improves the accuracy of answers and reduces model hallucinations, but also facilitates the updating of knowledge and the introduction of domain-specific knowledge. This is of great significance for the application of large models in various fields.

The problem of the illusion of large models has long been a focus of attention in the industry. Traditional solutions tend to focus on optimizing the internal structure of the model or adjusting the training method. However, RAG provides a new perspective on improving the accuracy of the answer through the retrieval of an external knowledge base. This approach opens up new possibilities and space for the application of large models.

It is worth noting that the applications of RAG are not limited to specific domains. Whether it is natural language processing, intelligent Q&A, or broader knowledge-based reasoning tasks, RAG has shown its unique advantages. This gives RAG a wide range of application prospects and is expected to be widely used in various fields in the future.

This collaborative research between Tongji University and Fudan University provides us with a powerful tool to solve the large model illusion problem. We expect that RAG will be further developed and improved in future research, injecting new vitality into the application of large models and the development of artificial intelligence.