Vikash
Sehwag

Publications

Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Model

WWW, 2025
Jie Ren, Kangrui Chen, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu

Large Language Models (LLMs) and Vision-Language Models (VLMs) have made significant advancements in a wide range of natural language processing and vision-language tasks. Access to large web-scale datasets has been a key factor in their success. However, concerns have been …

Masked Differential Privacy

ECCV, 2024
Sina Sajadmanesh, Vikash Sehwag, Lingjuan Lyu, Vivek Sharma, David Schneider, Saquib Sarfraz, Rainer Stiefelhagen

Privacy-preserving computer vision is an important emerg- ing problem in machine learning and artificial intelligence. The prevalent methods tackling this problem use differential privacy or anonymization and obfuscation techniques to protect the privacy of individuals. In b…

Finding a needle in a haystack: A Black-Box Approach to Invisible Watermark Detection

ECCV, 2024
Minzhou Pan*, Zhenting Wang, Xin Dong, Vikash Sehwag, Lingjuan Lyu, Xue Lin*

In this paper, we propose WaterMark Detection (WMD), the first invisible watermark detection method under a black-box and annotation-free setting. WMD is capable of detecting arbitrary watermarks within a given reference dataset using a clean non watermarked dataset as a ref…

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