
WWW 2026 ·
DRGW: Learning Disentangled Representations for Robust Graph Watermarking
Protecting graph ownership through robust, disentangled watermark representations.
Hello, I'm
Ph.D. Student
University of Chinese Academy of Sciences (UCAS)
I am a Ph.D. student at the University of Chinese Academy of Sciences, based at the Institute of Information Engineering, Chinese Academy of Sciences.
My research interests lie in AI safety and AI security.

WWW 2026 ·
Protecting graph ownership through robust, disentangled watermark representations.

USENIX Security 2026 ·
Verifying model ancestry through the consistency of knowledge evolution.

ICASSP 2026 ·
Learning secure, robust watermarks for graph signals while preserving their utility.
* Equal contribution † Corresponding author