模型开放性框架：促进人工智能中可复现性、透明性和可用性的完整性与开放性
The Model Openness Framework: Promoting Completeness and Openness for Reproducibility, Transparency, and Usability in Artificial Intelligence
AI总结：
本文提出模型开放性框架（MOF）及配套工具（MOT），通过三级分级系统评估机器学习模型的完整性与开放性，为模型生产者和消费者提供指导，以促进负责任AI研发和开放AI生态建设。
摘要：
生成式人工智能（AI）为研究和创新提供了众多机会，但其商业化引发了人们对于前沿AI模型透明性和安全性的担忧。大多数模型缺乏实现充分理解、审计和可复现性所需的必要组件，并且一些模型生产者在声称其模型为“开源”的同时使用限制性许可证。为解决这些问题，我们提出了模型开放性框架（Model Openness Framework，MOF），这是一个三级分级分类系统，遵循开放科学原则，根据机器学习模型的完整性和开放性对其进行评级。对于每个MOF等级，我们明确规定了模型开发生命周期中必须发布且须采用开放许可证的代码、数据和文档组件。此外，模型开放性工具（Model Openness Tool，MOT）提供了一个用户友好的参考实现，用于依据MOF分类系统评估模型的开放性和完整性。MOF和MOT共同为以下两方面提供了及时且实用的指导：（i）模型生产者增强其公开发布模型的开放性和完整性，以及（ii）模型消费者识别可被许可使用、研究、修改和再分发的开放模型及其组成组件。通过MOF，我们力求将完整性和开放性确立为负责任AI研究与开发的核心原则，并在蓬勃发展的开放AI生态系统中推广最佳实践。
英文摘要：
Generative artificial intelligence (AI) offers numerous opportunities for research and innovation, but its commercialization has raised concerns about the transparency and safety of frontier AI models. Most models lack the necessary components for full understanding, auditing, and reproducibility, and some model producers use restrictive licenses whilst claiming that their models are "open source". To address these concerns, we introduce the Model Openness Framework (MOF), a three-tiered ranked classification system that rates machine learning models based on their completeness and openness, following open science principles. For each MOF class, we specify code, data, and documentation components of the model development lifecycle that must be released and under which open licenses. In addition, the Model Openness Tool (MOT) provides a user-friendly reference implementation to evaluate the openness and completeness of models against the MOF classification system. Together, the MOF and MOT provide timely practical guidance for (i) model producers to enhance the openness and completeness of their publicly-released models, and (ii) model consumers to identify open models and their constituent components that can be permissively used, studied, modified, and redistributed. Through the MOF, we seek to establish completeness and openness as core tenets of responsible AI research and development, and to promote best practices in the burgeoning open AI ecosystem.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
