Analysis of Text Generation System Design Combining Retrieval Augmented Generation and Fine-Tuning Strategy

Text generation technology based on Pre-trained Language Model (PLM) has made significant progress in recent years, but it still faces many challenges such as semantic inconsistency and insufficient computing power. In view of this phenomenon, Retrieval Augmented Generation (RAG) and Fine-tuning strategy is studied, the general framework design for the text generation system of fusion strategy is put forward, several typical systems in specific fields are analyzed. The discussion of the realization and development direction of technology provides a reference for studying fusion strategy, which can improve the quality of text generation system design.