Dominik Hintersdorf

Orcid: 0000-0003-4976-6894

According to our database1, Dominik Hintersdorf authored at least 27 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2025
Finding Dori: Memorization in Text-to-Image Diffusion Models Is Less Local Than Assumed.
CoRR, July, 2025

Auditing and instructing text-to-image generation models on fairness.
AI Ethics, June, 2025

2024
Does CLIP Know My Face?
J. Artif. Intell. Res., 2024

Exploring the Adversarial Capabilities of Large Language Models.
CoRR, 2024

Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Exploiting Cultural Biases via Homoglyphs inText-to-Image Synthesis (Abstract Reprint).
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Defending Our Privacy with Backdoors.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023
Exploiting Cultural Biases via Homoglyphs in Text-to-Image Synthesis.
J. Artif. Intell. Res., 2023

Combining AI and AM - Improving approximate matching through transformer networks.
Digit. Investig., 2023

Leveraging Diffusion-Based Image Variations for Robust Training on Poisoned Data.
CoRR, 2023

Balancing Transparency and Risk: The Security and Privacy Risks of Open-Source Machine Learning Models.
CoRR, 2023

Image Classifiers Leak Sensitive Attributes About Their Classes.
CoRR, 2023

Fair Diffusion: Instructing Text-to-Image Generation Models on Fairness.
CoRR, 2023

SEGA: Instructing Diffusion using Semantic Dimensions.
CoRR, 2023

Balancing Transparency and Risk: An Overview of the Security and Privacy Risks of Open-Source Machine Learning Models.
Proceedings of the Bridging the Gap Between AI and Reality, 2023

SEGA: Instructing Text-to-Image Models using Semantic Guidance.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
The Stable Artist: Steering Semantics in Diffusion Latent Space.
CoRR, 2022

Rickrolling the Artist: Injecting Invisible Backdoors into Text-Guided Image Generation Models.
CoRR, 2022

The Biased Artist: Exploiting Cultural Biases via Homoglyphs in Text-Guided Image Generation Models.
CoRR, 2022

CLIPping Privacy: Identity Inference Attacks on Multi-Modal Machine Learning Models.
CoRR, 2022

Transformer-Boosted Anomaly Detection with Fuzzy Hashes.
CoRR, 2022

To Trust or Not To Trust Prediction Scores for Membership Inference Attacks.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks.
Proceedings of the International Conference on Machine Learning, 2022

Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021
Do Not Trust Prediction Scores for Membership Inference Attacks.
CoRR, 2021


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