Christian Schultze, Niklas Kerkfeld, Kara Kuebart, Princilia Weber, Moritz Wolter, and Felix Selgert, “Chronicling Germany: an annotated historical newspaper dataset,” arXiv.org, Jan. 30, 2024. https://arxiv.org/abs/2401.16845

Emad Bahrami, Gianpiero Francesca, and Juergen Gall, “How Much Temporal Long-Term Context is Needed for Action Segmentation?,” arXiv.org, Aug. 22, 2023. https://arxiv.org/abs/2308.11358

Olga Zatsarynna, Emad Bahrami, Yazan A. Farha, Gianpiero Francesca, and Juergen Gall, “Gated temporal diffusion for stochastic Long-Term dense anticipation,” arXiv (Cornell University), Jul. 2024, doi: 10.48550/arxiv.2407.11954.

Julian Spravil, Sebastian Houben, and Sven Behnke, “HyenaPixel: Global Image Context with Convolutions,” arXiv (Cornell University), Feb. 2024, doi: 10.48550/arxiv.2402.19305.

Jenia Jitsev et al., “OpenFlamingo: an Open-Source framework for training large autoregressive Vision-Language models,” arXiv (Cornell University), Jan. 2023, doi: 10.48550/arxiv.2308.01390.

Lars Hillebrand, Armin Berger, Tobias Deußer, Tim Dilmaghani, Mohamed Khaled, Bernd Kliem, Rüdiger Loitz, Maren Pielka, David Leonhard, Christian Bauckhage, and Rafel Sifa, “Improving Zero-Shot Text Matching for Financial Auditing with Large Language Models,” ACM Digital Library, Aug. 2023, doi: 10.1145/3573128.3609344

Marianna Nezhurina and Jenia Jitsev, “Language models scale reliably with over-training and on downstream  tasks,” arXiv (Cornell University), Mar. 2024, doi: 10.48550/arxiv.2403.08540.

Robert H. Schmitt, Dominik Wolfschläger, Jan-Henrik Woltersmann, and Lennart Stohrer, “Measurability of quality characteristics identified in latent spaces of Generative AI Models,” CIRP Annals, Jan. 2024, doi: 10.1016/j.cirp.2024.04.073.

Maren Pielka, Svetlana Schmidt, and Rafet Sifa, “Generating Prototypes for Contradiction Detection Using Large Language Models and Linguistic Rules,” IEEE Xplore, Dec. 2023, doi: 10.1109/bigdata59044.2023.10386499.

Maren Pielka, Jörn Hees, Bouthaina Soulef Abdou, Rafet Sifa, and Mohammad Majd Saad Al Deen, “Improving natural language inference in Arabic using transformer models and linguistically informed Pre-Training,” IEEE Conference Publication | IEEE Xplore, Dec. 05, 2023. https://ieeexplore.ieee.org/document/10371891

L. Hillebrand et al., “sustain.AI,” ACM Digital Library, Jun. 2023, doi: 10.1145/3594536.3595131.

Marianna Nezhurina et al., “Composing and validating Large-Scale datasets for training open foundation models for audio,” journal-article. Online. Available: https://mlforaudioworkshop.com/CompValDataFoundationModels.pdf

Yongli Mou et al., “Towards FAIR Data in Distributed Machine Learning Systems,” IEEE Global Communications Conference 2023, Dec. 2023, doi: 10.1109/globecom54140.2023.10437414.

Julian Spravil, Sebastian Houben, Sven Behnke, “Dynamic 3D Gaussians: Tracking by persistent dynamic view synthesis,” arXiv (Cornell University), Jan. 2023, doi: 10.48550/arxiv.2308.09713.

Julian Spravil, Sebastian Houben, Sven Behnke, “MASK4D: Mask transformer for 4D panoptic segmentation,” arXiv (Cornell University), Jan. 2023, doi: 10.48550/arxiv.2309.16133.

Veronica Lachi, Alice Moallemy-Oureh, Andreas Roth, and Pascal Welke, “Graph pooling provably improves expressivity,” OpenReview. https://openreview.net/forum?id=lR5NYB9zrv

Andreas Roth and Thomas Liebig, “Distilling influences to mitigate prediction churn in graph neural networks,” arXiv (Cornell University), Jan. 2023, doi: 10.48550/arxiv.2310.00946.

Yongli Mou, Jiahui Geng, Feng Zhou, Oya Beyan, Chunming Rong, and Stefan Decker, “pFedV: Mitigating Feature Distribution Skewness via Personalized Federated Learning with Variational Distribution Constraints,” in Lecture notes in computer science, 2023, pp. 283–294. doi: 10.1007/978-3-031-33377-4_22.

Janek Ebbers, Reinhold Haeb-Umbach, Paderborn University, Romain Serizel, and Universit´e de Lorraine, CNRS, Inria, Loria, “Post-Processing independent evaluation of sound event detection systems,” Journal-article, 2023. [Online]. https://dcase.community/documents/workshop2023/proceedings/DCASE2023Workshop_Ebbers_62.pdf

Mayara E. Bonani, Max Schwarz, and Sven Behnke, “Learning from SAM: Harnessing a Segmentation Foundation Model for Sim2Real Domain Adaptation through Regularization,” arXiv (Cornell University), Jan. 2023, doi: 10.48550/arxiv.2309.15562.

Helin Cao and Sven Behnke, “SLCF-Net: Sequential LiDAR-Camera Fusion for Semantic Scene Completion  using a 3D Recurrent U-Net,” arXiv (Cornell University), Mar. 2024, doi: 10.48550/arxiv.2403.08885.

Van Holland Leif, Ruben Bliersbach, Jan U. Müller, Patrick Stotko, and Reinhard Klein, “TraM-NeRF: Tracing Mirror and Near-Perfect Specular Reflections through Neural Radiance Fields,” arXiv (Cornell University), Jan. 2023, doi: 10.48550/arxiv.2310.10650.

David Stotko, Nils Wandel, and Reinhard Klein, “Physics-guided Shape-from-Template: Monocular Video Perception through Neural Surrogate Models,” arXiv (Cornell University), Jan. 2023, doi: 10.48550/arxiv.2311.12796.

Domenic Zingsheim and Reinhard Klein, “Learning subsurface scattering solutions of tightly-packed granular media using optimal transport,” Computers & Graphics, vol. 119, p. 103895, Feb. 2024, doi: 10.1016/j.cag.2024.103895.

Tiansi Dong and Rafet Sifa, “Word sense disambiguation as a game of neurosymbolic darts,” arXiv (Cornell University), Jan. 2023, doi: 10.48550/arxiv.2307.16663.

Moritz Wolter, Lokesh Veeramacheneni, Bettina Baeßler, Ulrike Attenberger and Barbara Wichtmann, “On the Stability of Neural Segmentation in Radiology“, ESANN, 2024,   

Saskia Rabich, Patrick Stotko, and Reinhard Klein, “FPO++: Efficient encoding and rendering of dynamic neural radiance fields by analyzing and enhancing Fourier PlenOctrees,” arXiv (Cornell University), Jan. 2023, doi: 10.48550/arxiv.2310.20710.

Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt; DataComp: In search of the next generation of multimodal datasets. NeurIPS 2023.

Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, Jenia Jitsev. LAION-5B: An open large-scale dataset for training next generation image-text models. Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 25278-25294.

Cedric Sanders, Andreas Roth, and Thomas Liebig. Curvature-based Pooling within Graph Neural Networks. arXiv preprint arXiv:2308.16516.

Andreas Roth and Thomas Liebig. Rank Collapse Causes Over-Smoothing and Over-Correlation in Graph Neural Networks. arXiv preprint arXiv:2308.16800.

Julian Tanke, Linguang Zhang, Amy Zhao, Chengcheng Tang, Yujun Cai, Lezi Wang, Po-Chen Wu, Juergen Gall, and Cem Keskin. Social Diffusion: Long-term Multiple Human Motion Anticipation.

Julian Kaltheuner, Patrick Stotko, and Reinhard Klein. Unified shape and appearance reconstruction with joint camera parameter refinement. Graphical Models, Volume 129, 2023.

Simon Bultmann, Raphael Memmesheimer, and Sven Behnke. External Camera-based Mobile Robot Pose Estimation for Collaborative Perception with Smart Edge Sensors in IEEE International Conference on Robotics and Automation (ICRA), London, UK, June 2023.

Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, and Jenia Jitsev. Reproducible scaling laws for contrastive language-image learning. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

Radu Alexandru Rosu and Sven Behnke. PermutoSDF: Fast Multi-View Reconstruction with Implicit Surfaces using Permutohedral Lattices. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, June 2023.