Albatross publications #

• Ahmed Anwar, Brian Moser, Dayananda Herurkar, Federico Raue, Vinit Hegiste, Tatjana Legler, and Andreas Dengel. “FedAD-Bench: A Unified Benchmark for Federated Unsupervised Anomaly Detection in Tabular Data.”
  arXiv preprint arXiv:2408.04442 (2024).
  arXiv
• Stanislav Frolov, Brian Moser, Sebastian Palacio, and Andreas Dengel “ObjBlur: A Curriculum Learning Approach With Progressive Object-Level Blurring for Improved Layout-to-Image Generation.”
  In Proceedings of the 32nd ACM International Conference on Multimedia. 2024, pp. 10621–10629.
  arXiv
• Lukas Helff, Felix Friedrich, Manuel Brack, Kristian Kersting, and Patrick Schramowski. “LLavaGuard: VLM-based Safeguards for Vision Dataset Curation and Safety Assessment.”
  In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 8322-8326. 2024.
  arXiv | Page | GitHub
• Brian B. Moser, Ahmed Anwar, Federico Raue, Stanislav Frolov, and Andreas Dengel. “Federated Learning for Blind Image Super-Resolution.”
  In International Conference on Neural Information Processing, pp. 316-331. Singapore: Springer Nature Singapore, 2024.
  arXiv
• Brian B. Moser, Federico Raue, Sebastian Palacio, Stanislav Frolov, and Andreas Dengel. “Latent dataset distillation with diffusion models.”
  arXiv preprint arXiv:2403.03881 (2024).
  arXiv
• Dayananda Herurkar, Federico Raue, and Andreas Dengel. “Tab-distillation: Impacts of dataset distillation on tabular data for outlier detection.”
  In Proceedings of the 5th ACM International Conference on AI in Finance, pp. 804-812. 2024.
  DFKI
• Brian Moser, Federico Raue, and Andreas Dengel. “A study in dataset pruning for image super-resolution.”
  In International Conference on Artificial Neural Networks. Springer. 2024, pp. 351–363.
  arXiv
• Brian Moser, Federico Raue, Tobias Christian Nauen, Stanislav Frolov, and Andreas Dengel. “Distill the best, ignore the rest: Improving dataset distillation with loss-value-based pruning.”
  In International Joint Conference on Neural Networks, June 30-July 5, Rome, Italy. IEEE, 2025.
  arXiv
• Tobias Christian Nauen, Sebastian Palacio, Federico Raue, and Andreas Dengel. “Which Transformer to Favor: A Comparative Analysis of Efficiency in Vision Transformers.”
  In 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 6955-6966. IEEE, 2025.
  arXiv
• Tobias Christian Nauen, Brian Moser, Federico Raue, Stanislav Frolov, and Andreas Dengel. “ForAug: Recombining Foregrounds and Backgrounds to Improve Vision Transformer Training with Bias Mitigation.”
  arXiv preprint arXiv:2503.09399 (2025).
  arXiv