GPTZero: Robust Detection of LLM-Generated Texts

• URL: http://arxiv.org/abs/2602.13042v1
• Date: Fri, 13 Feb 2026 15:53:45 GMT
• Title: GPTZero: Robust Detection of LLM-Generated Texts
• Authors: George Alexandru Adam, Alexander Cui, Edwin Thomas, Emily Napier, Nazar Shmatko, Jacob Schnell, Jacob Junqi Tian, Alekhya Dronavalli, Edward Tian, Dongwon Lee,
• Abstract summary: We introduce GPTZero, a state-of-the-art industrial AI detection solution, offering reliable discernment between human and AI-generated text.<n>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.
• Score: 35.450284723787554
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: 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.

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