On Seeding Watermarks to Detect Verbatim LLM Copy-Paste Responses
Large language models (LLMs) have made fluent essay writing, code drafting, and quiz answering instantly available to students at every level, from secondary school through graduate study. Many educators do not object to LLM use \emph{per~se}; what they need to detect is the case in which a student pastes the assignment prompt into a chatbot and submits the model's reply verbatim, without engaging with the work. Existing post-hoc AI-text detectors remain unreliable and have been shown to penalise non-native English writers, while output-side watermarks require cooperation from the model provider. We propose an alternative that the educator controls directly: an input-side watermark in whi...
| Authors | Aizierjiang Aiersilan, Artin Yousefi, Robert Pless |
|---|---|
| Primary category | cs.CR |
| Published | 7 May 2026 |
| Last updated at source | 7 August 2026 |
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