3 citations · 3 across the 12 of their papers we have counts for
14 papers
Probabilistic Verification of Voice Anti-Spoofing Models
Evgeny Kushnir, Alexandr Kozodaev, Dmitrii Korzh +3
Recent advances in generative models have amplified the risk of malicious misuse of speech synthesis technologies, enabling adversaries to impersonate target speakers and access se…
Contract And Conquer: How to Provably Compute Adversarial Examples for a Black-Box Model?
Anna Chistyakova, Mikhail Pautov
Black-box adversarial attacks are widely used as tools to test the robustness of deep neural networks against malicious perturbations of input data aimed at a specific change in th…
RandMark: On Random Watermarking of Visual Foundation Models
Anna Chistyakova, Mikhail Pautov
Being trained on large and diverse datasets, visual foundation models (VFMs) can be fine-tuned to achieve remarkable performance and efficiency in various downstream computer visio…
Towards Robust Speech Deepfake Detection via Human-Inspired Reasoning
Artem Dvirniak, Evgeny Kushnir, Dmitrii Tarasov +5
The modern generative audio models can be used by an adversary in an unlawful manner, specifically, to impersonate other people to gain access to private information. To mitigate t…
ActiveMark: on watermarking of visual foundation models via massive activations
Anna Chistyakova, Mikhail Pautov
Being trained on large and vast datasets, visual foundation models (VFMs) can be fine-tuned for diverse downstream tasks, achieving remarkable performance and efficiency in various…
Spread them Apart: Towards Robust Watermarking of Generated Content
Mikhail Pautov, Danil Ivanov, Andrey V. Galichin +2
Generative models that can produce realistic images have improved significantly in recent years. The quality of the generated content has increased drastically, so sometimes it is…