Queiroz, R., Sharma, D., Caldas, R., Czarnecki, K., Garcia, S., Berger, T., & Pelliccione, P. (2024). A driver-vehicle model for ADS scenario-based testing IEEE Transactions on Intelligent Transportation Systems, 14. https://doi.org/10.1109/TITS.2024.3373531 (Original work published 2024)
References
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2024
Thérien, B., Huang, C., Chow, A., & Czarnecki, K. (2024). Object Re-identification from Point Clouds Presented at the IEEE/CVF/Winter/Conference/on/Applications/of/Computer/Vision/(WACV) conference. IEEE. https://doi.org/https://doi.ieeecomputersociety.org/10.1109/WACV57701.2024.00819
2025
Wang, Y., Azadani, M. N., Sedwards, S., & Czarnecki, K. (2025). Leo-mini: An efficient multimodal large language model using conditional token reduction and mixture of multi-modal experts Presented at the Conference on Empirical Methods in Natural Language Processing (EMNLP) conference. Suzhou, China. https://doi.org/10.18653/v1/2025.emnlp-main.368 (Original work published 2025)
Berger, T., Mahmoud, W., Zahra, R. A., Vassilevski, I., Burger, A., Ji, W., … Czarnecki, K. (2025). Cost and Benefit of Tracing Features with Embedded Annotations ACM Transactions on Software Engineering and Methodology, 35(4). https://doi.org/10.1145/3746060 (Original work published 2026)
Huang, C., Abdelzad, V., Sedwards, S., & Czarnecki, K. (2025). VADet: Multi-Frame LiDAR 3D Object Detection Using Variable Aggregation Presented at the 2025 IEEE CVF Winter Conference on Applications of Computer Vision (WACV) conference. Tucson, AZ, USA: IEEE. https://doi.org/10.1109/WACV61041.2025.00079 (Original work published 2025)
Huang, C., & Czarnecki, K. (2025). MFSeg: Efficient Multi-frame 3D Semantic Segmentation Presented at the IEEE International Conference on Robotics and Automation (ICRA) conference. Atlanta, GA, USA: IEEE. https://doi.org/10.1109/ICRA55743.2025.11127629 (Original work published 2025)
Tang, M. Q., Sedwards, S., Huang, C., & Czarnecki, K. (2025). How Hard is Snow? A Paired Domain Adaptation Dataset for Clear and Snowy Weather: CADC+ Presented at the IEEE Intelligent Vehicles Symposium (IV) conference. Cluj, Romania: IEEE. https://doi.org/10.1109/IV64158.2025.11097651 (Original work published 2025)
Wang, Y., & Czarnecki, K. (2025). AiDe: Improving 3D Open-Vocabulary Semantic Segmentation by Aligned Vision-Language Learning Presented at the IEEE/CVF/Winter/Conference/on/Applications/of/Computer/Vision/(WACV) conference. Tucson, AZ, USA: IEEE. https://doi.org/10.1109/WACV61041.2025.00265 (Original work published 2025)
Zhang, R., Sun, C., Ning, M., Valiollahimehrizi, R., Lu, Y., Czarnecki, K., & Khajepour, A. (2025). Quantifying Learning Algorithm Uncertainties in Autonomous Driving Systems: Enhancing Safety through Polynomial Chaos Expansion and High-Definition Maps Accident Analysis & Prevention, 211, 11. https://doi.org/10.1016/j.aap.2024.107903 (Original work published 2025)
Hu, B. C., Di Sandro, A., Marsso, L., Czarnecki, K., & Chechik, M. (2025). Arguing Reliability of Machine Learning-based Components Presented at the IEEE Engineering Reliable Autonomous Systems (ERAS) conference. Worcester, MA, USA: IEEE. https://doi.org/10.1109/ERAS63351.2025.11135634 (Original work published 2026)