Guo Yixuan

Student, the University of Hong Kong

Laidlaw Research Poster- Guo Yixuan

This project investigates how canary-based attribution can still identify AI agents when their inputs are paraphrased. We find that adding a small amount of canary redundancy improves detection far more than tightening thresholds, making redundancy the key design lever for robust attribution.
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Sep 14, 2026