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Jahr: 2022
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  1. Zihan Ye; Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting

    Differentiable Meta logical Programming

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2211.11650, Pages 0-10, arXiv, 2022.

  2. Quentin Delfosse; Wolfgang Stammer; Thomas Rothenbacher; Dwarak Vittal; Kristian Kersting

    Boosting Object Representation Learning via Motion and Object Continuity

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2211.09771, Pages 0-10, arXiv, 2022.

  3. Lukas Struppek; Dominik Hintersdorf; Kristian Kersting

    Rickrolling the Artist: Injecting Invisible Backdoors into Text-Guided Image Generation Models

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2211.02408, Pages 0-10, arXiv, 2022.

  4. Felix Friedrich; Wolfgang Stammer; Patrick Schramowski; Kristian Kersting

    Revision Transformers: Getting RiT of No-Nos

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2210.10332, Pages 0-10, arXiv, 2022.

  5. Lukas Struppek; Dominik Hintersdorf; Kristian Kersting

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

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2209.08891, Pages 0-10, arXiv, 2022.

  6. Dominik Hintersdorf; Lukas Struppek; Kristian Kersting

    CLIPping Privacy: Identity Inference Attacks on Multi-Modal Machine Learning Models

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2209.07341, Pages 0-10, arXiv, 2022.

  7. Frieder Uhlig; Lukas Struppek; Dominik Hintersdorf; Kristian Kersting

    Transformer-Boosted Anomaly Detection with Fuzzy Hashes

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2208.11367, Pages 0-10, arXiv, 2022.

  8. Patrick Schramowski; Christopher Tauchmann; Kristian Kersting

    Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content?

    In: FAccT '22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency. ACM Conference on Fairness, Accountability, and …

  9. Lukas Struppek; Dominik Hintersdorf; Daniel Neider; Kristian Kersting

    Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash

    In: FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency. ACM Conference on Fairness, Accountability, and Transparency (ACM …

  10. Wolfgang Stammer; Marius Memmel; Patrick Schramowski; Kristian Kersting

    Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations

    In: IEEE/CVF Conference on Computer Vision and Pattern Recognition. International Conference on Computer Vision and Pattern Recognition (CVPR-2022), …

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