| Open x-embodiment: Robotic learning datasets and rt-x models A O'Neill, A Rehman, A Gupta, A Maddukuri, A Gupta, A Padalkar, A Lee, ... arXiv preprint arXiv:2310.08864, 2023 | 536* | 2023 |
| Octo: An open-source generalist robot policy OM Team, D Ghosh, H Walke, K Pertsch, K Black, O Mees, S Dasari, ... arXiv preprint arXiv:2405.12213, 2024 | 310* | 2024 |
| 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 | 146 | 2024 |
| From to : Your Language Model is Secretly a Q-Function R Rafailov, J Hejna, R Park, C Finn arXiv preprint arXiv:2404.12358, 2024 | 108* | 2024 |
| Few-Shot Preference Learning for Human-in-the-Loop RL J Hejna, D Sadigh 6th Annual Conference on Robot Learning, 2022 | 102 | 2022 |
| Extreme Q-Learning: MaxEnt RL without Entropy D Garg, J Hejna, M Geist, S Ermon International Conference on Learning Representations, 2023 | 80 | 2023 |
| Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning J Hejna, R Rafailov, H Sikchi, C Finn, S Niekum, WB Knox, D Sadigh The Twelfth International Conference on Learning Representations, 2023 | 79* | 2023 |
| Inverse preference learning: Preference-based rl without a reward function J Hejna, D Sadigh Advances in Neural Information Processing Systems 36, 18806-18827, 2023 | 51 | 2023 |
| Hierarchically decoupled imitation for morphological transfer D Hejna, L Pinto, P Abbeel International Conference on Machine Learning, 4159-4171, 2020 | 48 | 2020 |
| Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms R Rafailov, Y Chittepu, R Park, H Sikchi, J Hejna, B Knox, C Finn, ... arXiv preprint arXiv:2406.02900, 2024 | 44 | 2024 |
| Task-agnostic morphology evolution DJ Hejna III, P Abbeel, L Pinto International Conference on Learning Representations 2021, 2021 | 28 | 2021 |
| Distance Weighted Supervised Learning for Offline Interaction Data J Hejna, J Gao, D Sadigh International Conference on Machine Learning, 2023 | 17 | 2023 |
| Show, Don't Tell: Aligning Language Models with Demonstrated Feedback O Shaikh, M Lam, J Hejna, Y Shao, M Bernstein, D Yang arXiv preprint arXiv:2406.00888, 2024 | 14 | 2024 |
| Re-mix: Optimizing data mixtures for large scale imitation learning J Hejna, C Bhateja, Y Jiang, K Pertsch, D Sadigh arXiv preprint arXiv:2408.14037, 2024 | 9 | 2024 |
| Improving Long-Horizon Imitation through Instruction Prediction J Hejna, P Abbeel, L Pinto Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 7857-7865, 2023 | 7 | 2023 |
| Vision Language Models are In-Context Value Learners YJ Ma, J Hejna, C Fu, D Shah, J Liang, Z Xu, S Kirmani, P Xu, D Driess, ... The Thirteenth International Conference on Learning Representations, 2024 | 3 | 2024 |
| Improving Latent Representations via Explicit Disentanglement J Hejna, A Vangipuram, K Liu | 3 | 2020 |
| Robot Data Curation with Mutual Information Estimators J Hejna, S Mirchandani, A Balakrishna, A Xie, A Wahid, J Tompson, ... arXiv preprint arXiv:2502.08623, 2025 | 1 | 2025 |
| So You Think You Can Scale Up Autonomous Robot Data Collection? S Mirchandani, S Belkhale, J Hejna, E Choi, MS Islam, D Sadigh 8th Annual Conference on Robot Learning, 0 | 1* | |
| Efficiently Generating Expressive Quadruped Behaviors via Language-Guided Preference Learning J Clark, J Hejna, D Sadigh arXiv preprint arXiv:2502.03717, 2025 | | 2025 |
Dorsa SadighStanford Universitycs.stanford.edu의 이메일 확인됨
