Beyond the Final Actor: Modeling the Dual Roles of Creator and Editor for Fine-Grained LLM-Generated Text Detection

• URL: http://arxiv.org/abs/2604.04932v2
• Date: Tue, 07 Apr 2026 07:07:18 GMT
• Title: Beyond the Final Actor: Modeling the Dual Roles of Creator and Editor for Fine-Grained LLM-Generated Text Detection
• Abstract summary: RACE (Rhetorical Analysis for Creator-Editor Modeling) is a fine-grained detection method that characterizes the distinct signatures of creator and editor.<n> Experiments show that RACE outperforms 12 baselines in identifying fine-grained types with low false alarms.
• Score: 15.665001751819945
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The misuse of large language models (LLMs) requires precise detection of synthetic text. Existing works mainly follow binary or ternary classification settings, which can only distinguish pure human/LLM text or collaborative text at best. This remains insufficient for the nuanced regulation, as the LLM-polished human text and humanized LLM text often trigger different policy consequences. In this paper, we explore fine-grained LLM-generated text detection under a rigorous four-class setting. To handle such complexities, we propose RACE (Rhetorical Analysis for Creator-Editor Modeling), a fine-grained detection method that characterizes the distinct signatures of creator and editor. Specifically, RACE utilizes Rhetorical Structure Theory to construct a logic graph for the creator's foundation while extracting Elementary Discourse Unit-level features for the editor's style. Experiments show that RACE outperforms 12 baselines in identifying fine-grained types with low false alarms, offering a policy-aligned solution for LLM regulation.

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