| robosuite: A Modular Simulation Framework and Benchmark for Robot Learning Y Zhu, J Wong, A Mandlekar, R Martín-Martín, A Joshi, S Nasiriany, Y Zhu arXiv preprint arXiv:2009.12293v2, 2020 | 453 | 2020 |
| What Matters in Learning from Offline Human Demonstrations for Robot Manipulation A Mandlekar, D Xu, J Wong, S Nasiriany, C Wang, R Kulkarni, L Fei-Fei, ... arXiv preprint arXiv:2108.03298, 2021 | 449 | 2021 |
| Open X-Embodiment: Robotic Learning Datasets and RT-X Models A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ... arXiv preprint arXiv:2310.08864, 2023 | 362* | 2023 |
| Planning with goal-conditioned policies S Nasiriany, V Pong, S Lin, S Levine Advances in Neural Information Processing Systems, 14843-14854, 2019 | 267 | 2019 |
| Augmenting reinforcement learning with behavior primitives for diverse manipulation tasks S Nasiriany, H Liu, Y Zhu 2022 International Conference on Robotics and Automation (ICRA), 7477-7484, 2022 | 124 | 2022 |
| DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset A Khazatsky, K Pertsch, S Nair, A Balakrishna, S Dasari, S Karamcheti, ... arXiv preprint arXiv:2403.12945, 2024 | 118 | 2024 |
| PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs S Nasiriany, F Xia, W Yu, T Xiao, J Liang, I Dasgupta, A Xie, D Driess, ... arXiv preprint arXiv:2402.07872, 2024 | 81 | 2024 |
| MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations A Mandlekar, S Nasiriany, B Wen, I Akinola, Y Narang, L Fan, Y Zhu, ... 7th Annual Conference on Robot Learning, 2023 | 79 | 2023 |
| Learning and Retrieval from Prior Data for Skill-based Imitation Learning S Nasiriany, T Gao, A Mandlekar, Y Zhu arXiv preprint arXiv:2210.11435, 2022 | 41 | 2022 |
| RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots S Nasiriany, A Maddukuri, L Zhang, A Parikh, A Lo, A Joshi, A Mandlekar, ... arXiv preprint arXiv:2406.02523, 2024 | 40 | 2024 |
| Robot Learning on the Job: Human-in-the-Loop Autonomy and Learning During Deployment H Liu, S Nasiriany, L Zhang, Z Bao, Y Zhu arXiv preprint arXiv:2211.08416, 2022 | 40 | 2022 |
| DisCo RL: Distribution-conditioned reinforcement learning for general-purpose policies S Nasiriany, VH Pong, A Nair, A Khazatsky, G Berseth, S Levine arXiv preprint arXiv:2104.11707, 2021 | 22 | 2021 |
| A Comprehensive Guide to Machine Learning S Nasiriany, G Thomas, W Wang, A Yang, J Listgarten, A Sahai Department of Electrical Engineering and Computer Sciences University of …, 2019 | 18 | 2019 |
| Text Analysis and Automatic Triage of Posts in a Mental Health Forum E Asgari, S Nasiriany, MRK Mofrad Proceedings of the Third Workshop on Computational Linguistics and Clinical …, 2016 | 4 | 2016 |
| RT-Affordance: Affordances are Versatile Intermediate Representations for Robot Manipulation S Nasiriany, S Kirmani, T Ding, L Smith, Y Zhu, D Driess, D Sadigh, T Xiao arXiv preprint arXiv:2411.02704, 2024 | 3 | 2024 |
| PRIME: Scaffolding Manipulation Tasks with Behavior Primitives for Data-Efficient Imitation Learning T Gao, S Nasiriany, H Liu, Q Yang, Y Zhu arXiv preprint arXiv:2403.00929, 2024 | 3 | 2024 |
Yuke ZhuThe University of Texas at Austin, NVIDIA ResearchVahvistettu sähköpostiosoite verkkotunnuksessa cs.utexas.edu
