| [1] | Lai, Yuzhi and Yuan, Shenghai and Li, Peizheng and Zhang, Boya and Kiefer, Benjamin and Deng, Tianchen and Zell, Andreas. FAM-HRI: Foundation-Model Assisted Multimodal Human Robot Interaction Combining Gaze and Speech. , pages 10521-10534,May, 2026. Bibtex@ARTICLE{11534298,author = {Lai, Yuzhi and Yuan, Shenghai and Li, Peizheng and Zhang, Boya and Kiefer, Benjamin and Deng, Tianchen and Zell, Andreas}, journal = {IEEE Transactions on Automation Science and Engineering}, title = {FAM-HRI: Foundation-Model Assisted Multimodal Human Robot Interaction Combining Gaze and Speech}, year = {2026}, month = {May}, volume = {23}, number = {}, pages = {10521-10534}, doi = {10.1109/TASE.2026.3695438}, project = {abt_zell}, } |
| [2] | Kiefer, Benjamin and Augustin, Jan Lukas and Muhovi\v{c}, Jon and Jeong, Mingi and Wiliem, Arnold and Pers, Janez and Kristan, Matej and Li, Alberto Quattrini and Ter\v{s}ek, Matija and \v{S}ari\'c, Josip and Vats, Arpita and Hildebrand, Dominik and Rahim, Rafia and Karaaslan, Mahmut and Kaya, Ersin and Mashrur, Akib and Tang, Tze-Hsiang and Tsai, Chun-Ming and Hsieh, Jun-Wei and Chang, Ming-Ching and Jo, Wonwoo and Lee, Doyeon and Cao, Yusi and Li, Lingling and Nageli, Vinayak and Jamal, Arshad and Subrahmanyam, Gorthi Rama Krishna Sai and Maeng, Jemo and Lee, Seongju and Lee, Kyoobin and Liu, Xu and Jiao, Licheng and Sheikh, Jannik and Weinmann, Martin and Martinovi\'c, Ivan and Persch, Jose Mateus Raitz and Cheppally, Rahul Harsha and E Belviranli, Mehmet and Gahtidis, Dimitris and Chun, Hyewon and Lee, Sangmun and Gorczak, Philipp and Kim, Hansol and Jeon, Jeeyeon and Perez, Borja Carrillo and Wang, Jiahui and Park, Sangmin and Michel, Andreas and Kuester, Jannick and Felten, Bettina and Gross, Wolfgang and Feng, Yuan and Davis, Justin. 4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pages 8146-8156,Jun, 2026. [pdf]Bibtex@InProceedings{MaCVi_WS_2026,author = {Kiefer, Benjamin and Augustin, Jan Lukas and Muhovi\v{c}, Jon and Jeong, Mingi and Wiliem, Arnold and Pers, Janez and Kristan, Matej and Li, Alberto Quattrini and Ter\v{s}ek, Matija and \v{S}ari\'c, Josip and Vats, Arpita and Hildebrand, Dominik and Rahim, Rafia and Karaaslan, Mahmut and Kaya, Ersin and Mashrur, Akib and Tang, Tze-Hsiang and Tsai, Chun-Ming and Hsieh, Jun-Wei and Chang, Ming-Ching and Jo, Wonwoo and Lee, Doyeon and Cao, Yusi and Li, Lingling and Nageli, Vinayak and Jamal, Arshad and Subrahmanyam, Gorthi Rama Krishna Sai and Maeng, Jemo and Lee, Seongju and Lee, Kyoobin and Liu, Xu and Jiao, Licheng and Sheikh, Jannik and Weinmann, Martin and Martinovi\'c, Ivan and Persch, Jose Mateus Raitz and Cheppally, Rahul Harsha and E Belviranli, Mehmet and Gahtidis, Dimitris and Chun, Hyewon and Lee, Sangmun and Gorczak, Philipp and Kim, Hansol and Jeon, Jeeyeon and Perez, Borja Carrillo and Wang, Jiahui and Park, Sangmin and Michel, Andreas and Kuester, Jannick and Felten, Bettina and Gross, Wolfgang and Feng, Yuan and Davis, Justin}, title = {4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {Jun}, year = {2026}, pages = {8146-8156}, project = {abt_zell}, pdf = {https://openaccess.thecvf.com/content/CVPR2026W/MaCVi/papers/Kiefer_4th_Workshop_on_Maritime_Computer_Vision_MaCVi_Challenge_Overview_CVPRW_2026_paper.pdf}, } |
| [3] | Kiefer, Benjamin and Hildebrand, Dominik and Rahim, Rafia and Karaaslan, Mahmut and DeFilippo, Michael and Kaya, Ersin and Zell, Andreas. Real-Time Radar--Vision Association via Monocular Distance Estimation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pages 8157-8165,Jun, 2026. [pdf]Bibtex@InProceedings{MaCVi_WS_RTRVA,author = {Kiefer, Benjamin and Hildebrand, Dominik and Rahim, Rafia and Karaaslan, Mahmut and DeFilippo, Michael and Kaya, Ersin and Zell, Andreas}, title = {Real-Time Radar--Vision Association via Monocular Distance Estimation}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {Jun}, year = {2026}, pages = {8157-8165}, project = {abt_zell}, pdf = {https://openaccess.thecvf.com/content/CVPR2026W/MaCVi/papers/Kiefer_Real-Time_Radar--Vision_Association_via_Monocular_Distance_Estimation_CVPRW_2026_paper.pdf}, } |
| [4] | Kreis, Marten and Hildebrand, Dominik and Karaaslan, Mahmut and Rahim, Rafia and Zell, Andreas and Kaya, Ersin and Kiefer, Benjamin. Real-Time Fusion of Visual and Chart Data for Enhanced Maritime Vision. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pages 8166-8175,Jun, 2026. [pdf]Bibtex@InProceedings{MaCVi_WS_VisionChart,author = {Kreis, Marten and Hildebrand, Dominik and Karaaslan, Mahmut and Rahim, Rafia and Zell, Andreas and Kaya, Ersin and Kiefer, Benjamin}, title = {Real-Time Fusion of Visual and Chart Data for Enhanced Maritime Vision}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {Jun}, year = {2026}, pages = {8166-8175}, project = {abt_zell}, pdf = {https://openaccess.thecvf.com/content/CVPR2026W/MaCVi/papers/Kreis_Real-Time_Fusion_of_Visual_and_Chart_Data_for_Enhanced_Maritime_CVPRW_2026_paper.pdf}, } |
| [5] | Li, Peizheng and Zhang, Zhenghao and Holtz, David and Yu, Hang and Yang, Yutong and Lai, Yuzhi and Song, Rui and Geiger, Andreas and Zell, Andreas. SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Jun, 2026. [pdf , url]Bibtex@inproceedings{li2025spacedrive,title = {SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving}, author = {Li, Peizheng and Zhang, Zhenghao and Holtz, David and Yu, Hang and Yang, Yutong and Lai, Yuzhi and Song, Rui and Geiger, Andreas and Zell, Andreas}, booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2026}, month = {Jun}, pdf = {https://arxiv.org/pdf/2512.10719}, url = {https://zhenghao2519.github.io/SpaceDrive_Page/}, project = {abt_zell}, } |
| [6] | Hildebrand, Dominik and Kiefer, Benjamin and Zell, Andreas. Evaluating large language model compression: a comparative
analysis on state-of-the-art models across diverse hardware
platforms. Jul, 2026. [pdf]Bibtex@ARTICLE{Hildebrand2026-ELLMC,title = {Evaluating large language model compression: a comparative analysis on state-of-the-art models across diverse hardware platforms}, author = {Hildebrand, Dominik and Kiefer, Benjamin and Zell, Andreas}, abstract = {This work presents a systematic, empirical comparison of contemporary compression techniques for large language models (LLMs), namely quantization, pruning, and parameter-efficient fine-tuning (PEFT) using a representative set of open-source model families (Llama, Mistral, Phi and Qwen) and model scales (1.7 Billion to 70 Billion). Evaluation combined benchmarks (MMLU, SQuAD v2, TinyBenchmarks and WikiText), deployment metrics (peak memory, time-to-first-token, tokens/sec and maximum sequence lengths) and settings (multi-GPU clusters, single-GPU PC, laptop, and smartphone) to capture real-world trade-offs. Quantization often delivered the best wins for deployment feasibility---enabling single-device and mobile inference---but required careful per-model tuning and backend support to avoid throughput regressions. Pruning reduced parameter counts substantially but frequently incured large, even catastrophic, performance loss beyond moderate sparsity levels. Retraining partially mitigated this but did not uniformly close the gap to quantization. Finally, PEFT methods enabled models to match or outperform models with up to 18 times the parameters on SQuAD v2 while reducing storage as well as optimizer overhead and often improved task performance even when full fine-tuning failed.}, journal = {Artificial Intelligence Review}, month = {Jul}, year = {2026}, project = {abt_zell}, pdf = {https://link.springer.com/content/pdf/10.1007/s10462-026-11614-6.pdf}, } |
| [7] | Beffert, Max and Zell, Andreas. Low-Latency Quasi-Static Modeling of UAV Tether Aerodynamics. In 2026 International Conference on Unmanned Aircraft Systems (ICUAS), pages 1231-1238,2026. [pdf , url]Bibtex@INPROCEEDINGS{11598598,author = {Beffert, Max and Zell, Andreas}, booktitle = {2026 International Conference on Unmanned Aircraft Systems (ICUAS)}, title = {Low-Latency Quasi-Static Modeling of UAV Tether Aerodynamics}, year = {2026}, pages = {1231-1238}, keywords = {Power cables;Shape;Drag;System performance;Estimation;Autonomous aerial vehicles;Aerodynamics;Motors;System identification;Drones}, doi = {10.1109/ICUAS69441.2026.11598598}, pdf = {https://arxiv.org/pdf/2512.22588.pdf}, url = {https://github.com/cogsys-tuebingen/UAV-Tether-Modeling}, project = {abt_zell}, } |
| [8] | Canevaro, Alessandro and Yu, Hang and Schmidt, Julian and Li, Peizheng and Lindner, Silvan and Stork, Wilhelm and Martius, Georg and Jordan, Julian. Shift \& Drift: A Zero-Shot Benchmark for Generalizable and Robust Autonomous Driving Motion Planning. In 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)2026. [pdf]Bibtex@inproceedings{canevaro2026shift,title = {Shift \& Drift: A Zero-Shot Benchmark for Generalizable and Robust Autonomous Driving Motion Planning}, author = {Canevaro, Alessandro and Yu, Hang and Schmidt, Julian and Li, Peizheng and Lindner, Silvan and Stork, Wilhelm and Martius, Georg and Jordan, Julian}, booktitle = {2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year = {2026}, pdf = {https://arxiv.org/pdf/2607.07844}, organization = {IEEE}, project = {abt_zell}, } |
| [9] | Yu, Hang and Jin, Ye and Canevaro, Alessandro and Schmidt, Julian and Jordan, Julian and Li, Peizheng and Kaufeld, Marc and Lindner, Silvan and Betz, Johannes and Stork, Wilhelm. G2DP: Diffusion Planning with Spatio-Temporal Grid Guidance. In 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)2026. [pdf]Bibtex@inproceedings{yu2026g2dp,title = {G2DP: Diffusion Planning with Spatio-Temporal Grid Guidance}, author = {Yu, Hang and Jin, Ye and Canevaro, Alessandro and Schmidt, Julian and Jordan, Julian and Li, Peizheng and Kaufeld, Marc and Lindner, Silvan and Betz, Johannes and Stork, Wilhelm}, booktitle = {2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year = {2026}, pdf = {https://arxiv.org/pdf/2606.26017}, organization = {IEEE}, project = {abt_zell}, } |