| Rt-1: Robotics transformer for real-world control at scale A Brohan, N Brown, J Carbajal, Y Chebotar, J Dabis, C Finn, ... arXiv preprint arXiv:2212.06817, 2022 | 226 | 2022 |
| Accelerating Reinforcement Learning with Learned Skill Priors K Pertsch, Y Lee, JJ Lim Conference on Robot Learning (CoRL), 2020, 2020 | 172 | 2020 |
| Rt-2: Vision-language-action models transfer web knowledge to robotic control A Brohan, N Brown, J Carbajal, Y Chebotar, X Chen, K Choromanski, ... arXiv preprint arXiv:2307.15818, 2023 | 101 | 2023 |
| iPose: instance-aware 6D pose estimation of partly occluded objects OH Jafari*, SK Mustikovela*, K Pertsch, E Brachmann, C Rother Asian Conference on Computer Vision (ACCV), 2018, 2017 | 71* | 2017 |
| Demonstration-Guided Reinforcement Learning with Learned Skills K Pertsch, Y Lee, Y Wu, JJ Lim Conference on Robot Learning (CoRL), 2021, 2021 | 55* | 2021 |
| Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors K Pertsch, O Rybkin, F Ebert, C Finn, D Jayaraman, S Levine Conference on Neural Information Processing Systems (NeurIPS), 2020, 2020 | 54 | 2020 |
| Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments J Yamada, Y Lee, G Salhotra, K Pertsch, M Pflueger, GS Sukhatme, ... Conference on Robot Learning (CoRL), 2020, 2020 | 42 | 2020 |
| Skill-based Meta-Reinforcement Learning T Nam, SH Sun, K Pertsch, SJ Hwang, JJ Lim International Conference on Learning Representations (ICLR), 2022, 2022 | 34 | 2022 |
| Learning what you can do before doing anything O Rybkin*, K Pertsch*, KG Derpanis, K Daniilidis, A Jaegle International Conference on Learning Representations (ICLR), 2019, 2018 | 28* | 2018 |
| Keyframing the Future: Keyframe Discovery for Visual Prediction and Planning K Pertsch, O Rybkin, J Yang, K Derpanis, K Daniilidis, J Lim, A Jaegle 2nd Conference on Learning for Dynamics and Control (L4DC), 2020, 2020 | 25* | 2020 |
| 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 | 14 | 2023 |
| Task-Induced Representation Learning J Yamada, K Pertsch, A Gunjal, JJ Lim International Conference on Learning Representations (ICLR), 2022, 2022 | 9 | 2022 |
| PATO: Policy Assisted TeleOperation for Scalable Robot Data Collection S Dass, K Pertsch, H Zhang, Y Lee, JJ Lim, S Nikolaidis arXiv preprint arXiv:2212.04708, 2022 | 8 | 2022 |
| Q-transformer: Scalable offline reinforcement learning via autoregressive q-functions Y Chebotar, Q Vuong, A Irpan, K Hausman, F Xia, Y Lu, A Kumar, T Yu, ... arXiv preprint arXiv:2309.10150, 2023 | 7 | 2023 |
| SPRINT: Scalable Policy Pre-Training via Language Instruction Relabeling J Zhang, K Pertsch, J Zhang, JJ Lim arXiv preprint arXiv:2306.11886, 2023 | 6* | 2023 |
| Bootstrap your own skills: Learning to solve new tasks with large language model guidance J Zhang, J Zhang, K Pertsch, Z Liu, X Ren, M Chang, SH Sun, JJ Lim arXiv preprint arXiv:2310.10021, 2023 | 4 | 2023 |
| Cross-Domain Transfer via Semantic Skill Imitation K Pertsch, R Desai, V Kumar, F Meier, JJ Lim, D Batra, A Rai Conference on Robot Learning (CoRL), 2022, 2022 | 3 | 2022 |
| Transformer adapters for robot learning A Liang, I Singh, K Pertsch, J Thomason CoRL 2022 Workshop on Pre-training Robot Learning, 2022 | 3 | 2022 |
| Minimum description length skills for accelerated reinforcement learning J Zhang, K Pertsch, J Yang, JJ Lim Self-Supervision for Reinforcement Learning Workshop-ICLR 2021, 2021 | 3 | 2021 |
| Roboclip: one demonstration is enough to learn robot policies SA Sontakke, J Zhang, SMR Arnold, K Pertsch, E Bıyık, D Sadigh, C Finn, ... arXiv preprint arXiv:2310.07899, 2023 | 2 | 2023 |
Joseph J. LimAssociate Professor at KAISTAdresă de e-mail confirmată pe csail.mit.edu
