| On LLM Wizards: Identifying Large Language Models' Behaviors for Wizard of Oz Experiments J Fang, N Arechiga, K Namaoshi, N Bravo, C Hogan, DA Shamma arXiv preprint arXiv:2407.08067, 2024 | | 2024 |
| Bridging Design Gaps: A Parametric Data Completion Approach With Graph Guided Diffusion Models R Zhou, C Yuan, F Permenter, Y Zhang, N Arechiga, M Klenk, F Ahmed arXiv preprint arXiv:2406.11934, 2024 | | 2024 |
| Learning true objectives: Linear algebraic characterizations of identifiability in inverse reinforcement learning ML Shehab, A Aspeel, N Aréchiga, A Best, N Ozay 6th Annual Learning for Dynamics & Control Conference, 1266-1277, 2024 | | 2024 |
| Incorporating Logic in Online Preference Learning for Safe Personalization of Autonomous Vehicles R Karagulle, N Ozay, N Arechiga, J Decastro, A Best Proceedings of the 27th ACM International Conference on Hybrid Systems …, 2024 | 1 | 2024 |
| Data-Driven Car Drag Prediction With Depth and Normal Renderings C Yuan, F Permenter, N Arechiga, F Ahmed Journal of Mechanical Design 146, 051714-1, 2024 | | 2024 |
| Using LLMs to Model the Beliefs and Preferences of Targeted Populations K Namikoshi, A Filipowicz, DA Shamma, R Iliev, CL Hogan, N Arechiga arXiv preprint arXiv:2403.20252, 2024 | 1 | 2024 |
| System and method for contextualizing and improving understanding of web search results S Hakimi, CC Wu, ML Lee, N Arechiga US Patent 11,934,476, 2024 | | 2024 |
| A Safe Preference Learning Approach for Personalization with Applications to Autonomous Vehicles R Karagulle, N Aréchiga, A Best, J DeCastro, N Ozay IEEE Robotics and Automation Letters, 2024 | 1 | 2024 |
| Data-driven Car Drag Coefficient Prediction with Depth and Normal Renderings B Song, C Yuan, F Permenter, N Arechiga, F Ahmed American Society of Mechanical Engineers, 2024 | | 2024 |
| Training towards critical use: Learning to situate ai predictions relative to human knowledge A Kawakami, L Guerdan, Y Cheng, K Glazko, M Lee, S Carter, N Arechiga, ... Proceedings of The ACM Collective Intelligence Conference, 63-78, 2023 | 8 | 2023 |
| Actively adapting to driving environments based on human interactions S Kong, J DeCastro, N Arechiga, F Permenter US Patent 11,801,852, 2023 | | 2023 |
| A Preference Learning Approach to Develop Safe and Personalizable Autonomous Vehicles R Karagulle, N Aréchiga, A Best, J DeCastro, N Ozay arXiv preprint arXiv:2311.02099, 2023 | | 2023 |
| Robust Testing for Cyber-Physical Systems using Reinforcement Learning X Qin, N Aréchiga, J Deshmukh, A Best Proceedings of the 21st ACM-IEEE International Conference on Formal Methods …, 2023 | 2 | 2023 |
| Surrogate modeling of car drag coefficient with depth and normal renderings B Song, C Yuan, F Permenter, N Arechiga, F Ahmed International Design Engineering Technical Conferences and Computers and …, 2023 | 7 | 2023 |
| Drag-guided diffusion models for vehicle image generation N Arechiga, F Permenter, B Song, C Yuan arXiv preprint arXiv:2306.09935, 2023 | 7 | 2023 |
| System and method for machine-assisted collaboration in product design S Hakimi, S Carter, JA DeCastro, ES Sumner, Y Weng, N Arechiga US Patent App. 17/550,496, 2023 | | 2023 |
| Safety Guaranteed Preference Learning Approach for Autonomous Vehicles R Karagulle, N Arechiga, A Best, J Decastro, N Ozay Proceedings of the 26th ACM International Conference on Hybrid Systems …, 2023 | 2 | 2023 |
| Backpropagation through signal temporal logic specifications: Infusing logical structure into gradient-based methods K Leung, N Aréchiga, M Pavone The International Journal of Robotics Research 42 (6), 356-370, 2023 | 92 | 2023 |
| Systems and methods for prototype generation Y Weng, E Sumner, S Hakimi, N Arechiga, JA DeCastro US Patent App. 17/507,187, 2023 | 1 | 2023 |
| Systems and methods for preference elicitation on car designs JA DeCastro, S Hakimi, E Sumner, Y Weng, N Arechiga US Patent App. 17/508,110, 2023 | | 2023 |
