| 2025 | IJCNLP | IncogniText: Privacy-enhancing Conditional Text Anonymization via LLM-based Private Attribute Randomization. | Ahmed Frikha, Nassim Walha, Krishna Kanth Nakka, Ricardo Mendes, Xue Jiang, Xuebing Zhou |
| 2025 | IJCNLP | PII-Scope: A Comprehensive Study on Training Data Privacy Leakage in Pretrained LLMs. | Krishna Kanth Nakka, Ahmed Frikha, Ricardo Mendes, Xue Jiang, Xuebing Zhou |
| 2025 | MICCAI | Mammo-SAE : Interpreting Breast Cancer Concept Learning with Sparse Autoencoders. | Krishna Kanth Nakka |
| 2025 | WACV | NAT: Learning to Attack Neurons for Enhanced Adversarial Transferability. | Krishna Kanth Nakka, Alexandre Alahi |
| 2024 | CVPR | Federated Hyperparameter Optimization through Reward-Based Strategies: Challenges and Insights. | Krishna Kanth Nakka, Ahmed Frikha, Ricardo Mendes, Xue Jiang, Xuebing Zhou |
| 2022 | ECCV | Universal, Transferable Adversarial Perturbations for Visual Object Trackers. | Krishna Kanth Nakka, Mathieu Salzmann |
| 2020 | ACCV | Towards Robust Fine-Grained Recognition by Maximal Separation of Discriminative Features. | Krishna Kanth Nakka, Mathieu Salzmann |
| 2020 | ECCV | Indirect Local Attacks for Context-Aware Semantic Segmentation Networks. | Krishna Kanth Nakka, Mathieu Salzmann |
| 2019 | ICCV | Detecting the Unexpected via Image Resynthesis. | Krzysztof Lis, Krishna Kanth Nakka, Pascal Fua, Mathieu Salzmann |
| 2018 | BMVC | Deep Attentional Structured Representation Learning for Visual Recognition. | Krishna Kanth Nakka, Mathieu Salzmann |