Pre-trained models (PM) have achieved promising results in content generation. However, the space for human creativity and imagination is endless, and it is still unclear whether the existing models can meet the needs. Model-generated content faces uncontrollable responsibility and potential unethical problems. This paper presents the MetaAID 2.0 framework, dedicated to human-controllable PM information flow. Through the PM information flow, humans can autonomously control their creativity. Through the Universal Resource Identifier extension (URI-extension), the responsibility of the model outputs can be controlled. Our framework includes modules for handling multimodal data and supporting transformation and generation. The URI-extension consists of URI, detailed description, and URI embeddings, and supports fuzzy retrieval of model outputs. Based on this framework, we conduct experiments on PM information flow and URI embeddings, and the results demonstrate the good performance of our system.

翻译：预训练模型在内容生成领域取得了令人瞩目的成果。然而，人类创造力与想象力的空间是无限的，现有模型能否满足这些需求仍不明朗。模型生成的内容面临不可控责任与潜在的伦理问题。本文提出MetaAID 2.0框架，专注于实现人控预训练模型信息流。通过预训练模型信息流，人类可自主控制其创造力；通过统一资源标识符扩展（URI-extension），模型输出的责任可控性得以实现。本框架包含处理多模态数据及支持转换与生成的模块。URI-extension由URI、详细描述及URI嵌入向量组成，支持对模型输出的模糊检索。基于该框架，我们对预训练模型信息流及URI嵌入向量进行了实验，结果表明系统性能优异。