| Fair Diffusion: Instructing Text-to-Image Generation Models on Fairness F Friedrich, M Brack, L Struppek, D Hintersdorf, P Schramowski, ... arXiv preprint arXiv:2302.10893, 2023 | 49 | 2023 |
| Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash L Struppek, D Hintersdorf, D Neider, K Kersting ACM Conference on Fairness, Accountability, and Transparency (FAccT), 58-69, 2022 | 36 | 2022 |
| Plug & Play Attacks: Towards Robust and Flexible Model Inversion L Struppek, D Hintersdorf, ADA Correia, A Adler, K Kersting International Conference on Machine Learning (ICML) 162, 20522-20545, 2022 | 35* | 2022 |
| SEGA: Instructing Text-to-Image Models using Semantic Guidance M Brack, F Friedrich, D Hintersdorf, L Struppek, P Schramowski, ... Conference on Neural Information Processing Systems (NeurIPS), 2023 | 34* | 2023 |
| Exploiting Cultural Biases via Homoglyphs in Text-to-Image Synthesis L Struppek, D Hintersdorf, F Friedrich, M Brack, P Schramowski, ... Journal of Artificial Intelligence Research (JAIR) 78, 1017-1068, 2023 | 31* | 2023 |
| Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis L Struppek, D Hintersdorf, K Kersting International Conference on Computer Vision (ICCV), 2023 | 29* | 2023 |
| To Trust or Not To Trust Prediction Scores for Membership Inference Attacks D Hintersdorf, L Struppek, K Kersting International Joint Conference on Artificial Intelligence (IJCAI), 3043-3049, 2021 | 9* | 2021 |
| Does CLIP Know My Face? D Hintersdorf, L Struppek, M Brack, F Friedrich, P Schramowski, ... Journal of Artificial Intelligence Research (JAIR), 2024 | 5* | 2024 |
| Sparsely-gated Mixture-of-Expert Layers for CNN Interpretability S Pavlitskaya, C Hubschneider, L Struppek, JM Zöllner International Joint Conference on Neural Networks (IJCNN), 2023 | 4* | 2023 |
| Leveraging Diffusion-Based Image Variations for Robust Training on Poisoned Data L Struppek, MB Hentschel, C Poth, D Hintersdorf, K Kersting Conference on Neural Information Processing Systems (NeurIPS) - Workshop on …, 2023 | 3 | 2023 |
| Defending Our Privacy With Backdoors D Hintersdorf, L Struppek, D Neider, K Kersting Conference on Neural Information Processing Systems (NeurIPS) - Workshop on …, 2023 | 2 | 2023 |
| Exploring the Adversarial Capabilities of Large Language Models L Struppek, MH Le, D Hintersdorf, K Kersting International Conference on Learning Representations (ICLR) - Workshop on …, 2024 | 1 | 2024 |
| Combining AI and AM — Improving Approximate Matching through Transformer Networks F Uhlig, L Struppek, D Hintersdorf, T Göbel, H Baier, K Kersting Forensic Science International: Digital Investigation 45, 301570, 2023 | 1 | 2023 |
| Class Attribute Inference Attacks: Inferring Sensitive Class Information by Diffusion-Based Attribute Manipulations L Struppek, D Hintersdorf, F Friedrich, M Brack, P Schramowski, ... arXiv preprint arXiv:2303.09289, 2023 | 1* | 2023 |
| CollaFuse: Navigating Limited Resources and Privacy in Collaborative Generative AI D Zipperling, S Allmendinger, L Struppek, N Kühl European Conference on Information Systems (ECIS), 2024 | | 2024 |
| Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks L Struppek, D Hintersdorf, K Kersting International Conference on Learning Representations (ICLR), 2024 | | 2024 |
| Balancing Transparency and Risk: The Security and Privacy Risks of Open-Source Machine Learning Models D Hintersdorf, L Struppek, K Kersting AISoLA: Bridging the Gap Between AI and Reality, 2023 | | 2023 |
| Investigating the Risks of Client-Side Scanning for the Use Case NeuralHash D Hintersdorf, L Struppek, D Neider, K Kersting 🏆 IEEE Symposium on Security and Privacy - Workshop on Technology and …, 2022 | | 2022 |
Kristian KerstingProfessor of AI & ML, TU Darmstadt, Co-Director hessian.ai, DFKI, Germany, CLAIRE & ELLISVerified email at cs.tu-darmstadt.de
