While historical considerations surrounding text authenticity revolved primarily around plagiarism, the advent of large language models (LLMs) has introduced a new challenge: distinguishing human-authored from AI-generated text. This shift raises significant concerns, including the undermining of skill evaluations, the mass-production of low-quality content, and the proliferation of misinformation. Addressing these issues, we introduce GPTZero a state-of-the-art industrial AI detection solution, offering reliable discernment between human and LLM-generated text. Our key contributions include: introducing a hierarchical, multi-task architecture enabling a flexible taxonomy of human and AI texts, demonstrating state-of-the-art accuracy on a variety of domains with granular predictions, and achieving superior robustness to adversarial attacks and paraphrasing via multi-tiered automated red teaming. GPTZero offers accurate and explainable detection, and educates users on its responsible use, ensuring fair and transparent assessment of text.

翻译：历史上关于文本真实性的考量主要围绕剽窃问题展开，而大型语言模型（LLMs）的出现带来了新的挑战：如何区分人类创作与AI生成的文本。这一转变引发了多重严峻关切，包括技能评估体系的瓦解、低质量内容的大规模生产以及虚假信息的扩散。针对这些问题，我们推出了GPTZero——一种先进的工业级AI检测解决方案，能够可靠地区分人类与LLM生成的文本。我们的核心贡献包括：提出分层多任务架构以实现灵活的人类与AI文本分类体系；在多样化领域实现具有细粒度预测能力的顶尖检测精度；通过多层自动化红队测试，显著提升对抗性攻击与文本改写的鲁棒性。GPTZero提供精准且可解释的检测结果，同时指导用户进行负责任的使用，确保文本评估的公平性与透明度。