PhD student, Department of Computer Science, University of Maryland, College Park
2 papers at NeurIPS 2025
A technical report detailing a NeurIPS competition testing the robustness of popular watermarks and practical guidance for future development.
We propose adversarial paraphrasing: a training-free, transferable attack that universally humanizes AI-generated text by using an off-the-shelf LLM as a paraphraser, guided by an AI text detector.