15 citations · 22 across the 6 of their papers we have counts for
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cs.LG2026
Caliber: Cross-Architecture Extraction-Cost Control for Score-Returning APIs
Chi Wang, Hanwen Wang, Yu Xia +2
We present Caliber, an output-perturbation defense against model extraction that formulates noise selection as a calibration problem: how much the defense degrades the supervision…
cs.LG2025
Catch-Only-One: Non-Transferable Examples for Model-Specific Authorization
Zihan Wang, Zhiyong Ma, Zhongkui Ma +5
Recent AI regulations increasingly emphasize the need for mechanisms that preserve the utility of data for AI innovation while preventing misuse, particularly by enforcing purpose…
cs.LG2025★ 7 cited
Uncovering Gradient Inversion Risks in Practical Language Model Training
Xinguo Feng, Zhongkui Ma, Zihan Wang +4
The gradient inversion attack has been demonstrated as a significant privacy threat to federated learning (FL), particularly in continuous domains such as vision models. In contras…