Do Not Trust Prediction Scores for Membership Inference Attacks. - Dominik Hintersdorf; Lukas Struppek; Kristian Kersting (CoRR, 2021)

Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash. - Lukas Struppek; Dominik Hintersdorf; Daniel Neider; Kristian Kersting (FAccT, 2022)

Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks. - Lukas Struppek; Dominik Hintersdorf; Antonio De Almeida Correia; Antonia Adler; Kristian Kersting (ICML, 2022)

To Trust or Not To Trust Prediction Scores for Membership Inference Attacks. - Dominik Hintersdorf; Lukas Struppek; Kristian Kersting (IJCAI, 2022)

Balancing Expert Utilization in Mixture-of-Experts Layers Embedded in CNNs. - Svetlana Pavlitskaya; Christian Hubschneider; Lukas Struppek; J. Marius Zöllner (CoRR, 2022)

Transformer-Boosted Anomaly Detection with Fuzzy Hashes. - Frieder Uhlig; Lukas Struppek; Dominik Hintersdorf; Kristian Kersting (CoRR, 2022)

CLIPping Privacy: Identity Inference Attacks on Multi-Modal Machine Learning Models. - Dominik Hintersdorf; Lukas Struppek; Kristian Kersting (CoRR, 2022)

The Biased Artist: Exploiting Cultural Biases via Homoglyphs in Text-Guided Image Generation Models. - Lukas Struppek; Dominik Hintersdorf; Kristian Kersting (CoRR, 2022)

Rickrolling the Artist: Injecting Invisible Backdoors into Text-Guided Image Generation Models. - Lukas Struppek; Dominik Hintersdorf; Kristian Kersting (CoRR, 2022)

Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis. - Lukas Struppek; Dominik Hintersdorf; Kristian Kersting (ICCV, 2023)

Sparsely-gated Mixture-of-Expert Layers for CNN Interpretability. - Svetlana Pavlitska; Christian Hubschneider; Lukas Struppek; J. Marius Zöllner (IJCNN, 2023)

SEGA: Instructing Text-to-Image Models using Semantic Guidance. - Manuel Brack; Felix Friedrich; Dominik Hintersdorf; Lukas Struppek; Patrick Schramowski; Kristian Kersting (NeurIPS, 2023)

Balancing Transparency and Risk: An Overview of the Security and Privacy Risks of Open-Source Machine Learning Models. - Dominik Hintersdorf; Lukas Struppek; Kristian Kersting (AISoLA (Selected Papers), 2023)

SEGA: Instructing Diffusion using Semantic Dimensions. - Manuel Brack; Felix Friedrich; Dominik Hintersdorf; Lukas Struppek; Patrick Schramowski; Kristian Kersting (CoRR, 2023)

Fair Diffusion: Instructing Text-to-Image Generation Models on Fairness. - Felix Friedrich; Patrick Schramowski; Manuel Brack; Lukas Struppek; Dominik Hintersdorf; Sasha Luccioni; Kristian Kersting (CoRR, 2023)

Image Classifiers Leak Sensitive Attributes About Their Classes. - Lukas Struppek; Dominik Hintersdorf; Felix Friedrich; Manuel Brack; Patrick Schramowski; Kristian Kersting (CoRR, 2023)

Balancing Transparency and Risk: The Security and Privacy Risks of Open-Source Machine Learning Models. - Dominik Hintersdorf; Lukas Struppek; Kristian Kersting (CoRR, 2023)

Leveraging Diffusion-Based Image Variations for Robust Training on Poisoned Data. - Lukas Struppek; Martin B. Hentschel; Clifton Poth; Dominik Hintersdorf; Kristian Kersting (CoRR, 2023)

Combining AI and AM - Improving approximate matching through transformer networks. - Frieder Uhlig; Lukas Struppek; Dominik Hintersdorf; Thomas Göbel; Harald Baier; Kristian Kersting (Digit. Investig., 2023)

Exploiting Cultural Biases via Homoglyphs in Text-to-Image Synthesis. - Lukas Struppek; Dominik Hintersdorf; Felix Friedrich; Manuel Brack; Patrick Schramowski; Kristian Kersting (J. Artif. Intell. Res., 2023)

Defending Our Privacy with Backdoors. - Dominik Hintersdorf; Lukas Struppek; Daniel Neider; Kristian Kersting (ECAI, 2024)

Collafuse: Navigating Limited Resources and Privacy in Collaborative Generative AI. - Domenique Zipperling; Simeon Allmendinger; Lukas Struppek; Niklas Kühl 001 (ECIS, 2024)

Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks. - Lukas Struppek; Dominik Hintersdorf; Kristian Kersting (ICLR, 2024)

Exploiting Cultural Biases via Homoglyphs inText-to-Image Synthesis (Abstract Reprint). - Lukas Struppek; Dominik Hintersdorf; Felix Friedrich; Manuel Brack; Patrick Schramowski; Kristian Kersting (IJCAI, 2024)

Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models. - Dominik Hintersdorf; Lukas Struppek; Kristian Kersting; Adam Dziedzic; Franziska Boenisch (NeurIPS, 2024)

Exploring the Adversarial Capabilities of Large Language Models. - Lukas Struppek; Minh Hieu Le; Dominik Hintersdorf; Kristian Kersting (CoRR, 2024)

CollaFuse: Collaborative Diffusion Models. - Simeon Allmendinger; Domenique Zipperling; Lukas Struppek; Niklas Kühl 001 (CoRR, 2024)

Navigating Shortcuts, Spurious Correlations, and Confounders: From Origins via Detection to Mitigation. - David Steinmann; Felix Divo; Maurice Kraus; Antonia Wüst; Lukas Struppek; Felix Friedrich; Kristian Kersting (CoRR, 2024)

Does CLIP Know My Face? - Dominik Hintersdorf; Lukas Struppek; Manuel Brack; Felix Friedrich; Patrick Schramowski; Kristian Kersting (J. Artif. Intell. Res., 2024)

Auditing and instructing text-to-image generation models on fairness. - Felix Friedrich; Manuel Brack; Lukas Struppek; Dominik Hintersdorf; Patrick Schramowski; Sasha Luccioni; Kristian Kersting (AI Ethics, 2025)

Finding Dori: Memorization in Text-to-Image Diffusion Models Is Less Local Than Assumed. - Antoni Kowalczuk; Dominik Hintersdorf; Lukas Struppek; Kristian Kersting; Adam Dziedzic; Franziska Boenisch (CoRR, 2025)