Thaddäus Wiedemer

According to our database, Thaddäus Wiedemer authored at least 14 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

A Very Big Video Reasoning Suite.

Maijunxian Wang, Ruisi Wang, Juyi Lin, Ran Ji, Thaddäus Wiedemer, Qingying Gao, Dezhi Luo, Yaoyao Qian, Lianyu Huang, Zelong Hong, Jiahui Ge, Qianli Ma, Hang He, Yifan Zhou, Lingzi Guo, Lantao Mei, Jiachen Li, Hanwen Xing, Tianqi Zhao, Fengyuan Yu, Weihang Xiao, Yizheng Jiao, Jianheng Hou, Danyang Zhang, Pengcheng Xu, Boyang Zhong, Zehong Zhao, Gaoyun Fang, John Kitaoka, Yile Xu, Hua Xu, Kenton Blacutt, Tin Nguyen, Siyuan Song, Haoran Sun, Shaoyue Wen, Linyang He, Runming Wang, Yanzhi Wang, Mengyue Yang, Ziqiao Ma, Raphaël Millière, Freda Shi, Nuno Vasconcelos, Daniel Khashabi, Alan L. Yuille, Yilun Du, Ziming Liu, Bo Li, Dahua Lin, Ziwei Liu, Vikash Kumar, Yijiang Li, Lei Yang, Zhongang Cai, Hokin Deng

CoRR, February, 2026

MentisOculi: Revealing the Limits of Reasoning with Mental Imagery.

Jana Zeller, Thaddäus Wiedemer, Fanfei Li, Thomas Klein, Prasanna Mayilvahanan, Matthias Bethge, Felix A. Wichmann, Ryan Cotterell, Wieland Brendel

CoRR, February, 2026

2025

MATH-Beyond: A Benchmark for RL to Expand Beyond the Base Model.

Prasanna Mayilvahanan, Ricardo Dominguez-Olmedo, Thaddäus Wiedemer, Wieland Brendel

CoRR, October, 2025

Video models are zero-shot learners and reasoners.

Thaddäus Wiedemer, Yuxuan Li, Paul Vicol, Shixiang Shane Gu, Nick Matarese, Kevin Swersky, Been Kim, Priyank Jaini, Robert Geirhos

CoRR, September, 2025

Pretraining Frequency Predicts Compositional Generalization of CLIP on Real-World Tasks.

Thaddäus Wiedemer, Yash Sharma, Ameya Prabhu, Matthias Bethge, Wieland Brendel

CoRR, February, 2025

LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws.

Prasanna Mayilvahanan, Thaddäus Wiedemer, Sayak Mallick, Matthias Bethge, Wieland Brendel

Proceedings of the Forty-second International Conference on Machine Learning, 2025

VGGSounder: Audio-Visual Evaluations for Foundation Models.

Daniil Zverev, Thaddäus Wiedemer, Ameya Prabhu, Matthias Bethge, Wieland Brendel, A. Sophia Koepke

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

In Search of Forgotten Domain Generalization.

Prasanna Mayilvahanan, Roland S. Zimmermann, Thaddäus Wiedemer, Evgenia Rusak, Attila Juhos, Matthias Bethge, Wieland Brendel

Proceedings of the Proceedings on "I Can't Believe It's Not Better: Challenges in Applied Deep Learning" at ICLR 2025 Workshops, 2025

2024

Scale Learning in Scale-Equivariant Convolutional Networks.

Mark Basting, Robert-Jan Bruintjes, Thaddäus Wiedemer, Matthias Kümmerer, Matthias Bethge, Jan van Gemert

Proceedings of the 19th International Joint Conference on Computer Vision, 2024

Provable Compositional Generalization for Object-Centric Learning.

Thaddäus Wiedemer, Jack Brady, Alexander Panfilov, Attila Juhos, Matthias Bethge, Wieland Brendel

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Does CLIP's generalization performance mainly stem from high train-test similarity?

Prasanna Mayilvahanan, Thaddäus Wiedemer, Evgenia Rusak, Matthias Bethge, Wieland Brendel

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Compositional Generalization from First Principles.

Thaddäus Wiedemer, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Few-Shot Supervised Prototype Alignment for Pedestrian Detection on Fisheye Images.

Thaddäus Wiedemer, Stefan Wolf, Arne Schumann, Kaisheng Ma, Jürgen Beyerer

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2019

Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks.

Jörg Wagner, Jan Mathias Köhler, Tobias Gindele, Leon Hetzel, Jakob Thaddäus Wiedemer, Sven Behnke

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019