基于内在质量约束的文本生成和评价综述

Recently, the outstanding text generation language models represented by ChatGPT, which can adapt to complex scenes and meet various application demands of human beings, has become the focuses of both the academic and industrial circles. However, the advantage of large language models (LLM) such as ChatGPT that are highly faithful to user intent implies some factual errors, and it is also necessary to rely on prompt content to control the detailed generation quality and domain adaptability, so it is still of great significance to study text generation with intrinsic quality constraints as the core. Based on the comparative study of key content generation models and technologies in recent years, this paper defined the basic form of text generation with intrinsic quality constraints, and six quality features based on“credibility, expressiveness and elegance”. In view of these 6 quality features, we provided analysis and comparison of generator mod⁃ el design and related algorithms. Besides, various automatic and human evaluation methods for different intrinsic quality features are summarized. Finally, this paper looks forward to the future research directions of intrinsic quality constraint technology.