| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context https://arxiv.org/abs/2403.05530 | 2766* | 2024 |
| Gemma 2: Improving open language models at a practical size G Team, M Riviere, S Pathak, PG Sessa, C Hardin, S Bhupatiraju, ... arXiv preprint arXiv:2408.00118 | 1375 | 2024 |
| Legibility and predictability of robot motion AD Dragan, KCT Lee, SS Srinivasa 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI … | 981 | 2013 |
| Cooperative Inverse Reinforcement Learning D Hadfield-Menell, A Dragan, P Abbeel, S Russell Neural Information Processing Systems (NIPS) | 965 | 2016 |
| CHOMP: Covariant Hamiltonian Optimization for Motion Planning M Zucker, N Ratliff, AD Dragan, M Pivtoraiko, M Klingensmith, C Dellin, ... International Journal of Robotics Research | 957 | 2013 |
| Open problems and fundamental limitations of reinforcement learning from human feedback S Casper, X Davies, C Shi, TK Gilbert, J Scheurer, J Rando, R Freedman, ... arXiv preprint arXiv:2307.15217 | 754 | 2023 |
| Planning for autonomous cars that leverage effects on human actions. D Sadigh, S Sastry, SA Seshia, AD Dragan Robotics: Science and systems 2, 1-9 | 696 | 2016 |
| On the utility of learning about humans for human-ai coordination M Carroll, R Shah, MK Ho, T Griffiths, S Seshia, P Abbeel, A Dragan Advances in neural information processing systems 32 | 589 | 2019 |
| Inverse reward design D Hadfield-Menell, S Milli, P Abbeel, SJ Russell, A Dragan Advances in neural information processing systems 30 | 574 | 2017 |
| A policy-blending formalism for shared control AD Dragan, SS Srinivasa The International Journal of Robotics Research 32 (7), 790-805 | 495 | 2013 |
| Active preference-based learning of reward functions D Sadigh, AD Dragan, S Sastry, S Seshia RSS | 476 | 2017 |
| Effects of robot motion on human-robot collaboration AD Dragan, S Bauman, J Forlizzi, SS Srinivasa Proceedings of the tenth annual ACM/IEEE international conference on human … | 436 | 2015 |
| Managing extreme AI risks amid rapid progress Y Bengio, G Hinton, A Yao, D Song, P Abbeel, T Darrell, YN Harari, ... Science 384 (6698), 842-845 | 424 | 2024 |
| SQIL: imitation learning via regularized behavioral cloning S Reddy, AD Dragan, S Levine arXiv preprint arXiv:1905.11108 2 (5) | 414* | 2019 |
| On stochastic optimal control and reinforcement learning by approximate inference K Rawlik, M Toussaint, S Vijayakumar Proceedings of Robotics: Science and Systems VIII | 401 | 2012 |
| Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities G Comanici, E Bieber, M Schaekermann, I Pasupat, N Sachdeva, I Dhillon, ... arXiv preprint arXiv:2507.06261 | 382 | 2025 |
| Toward seamless human-robot handovers K Strabala, MK Lee, A Dragan, J Forlizzi, SS Srinivasa, M Cakmak, ... Journal of Human-Robot Interaction 2 (1), 112-132 | 367 | 2013 |
| Hierarchical game-theoretic planning for autonomous vehicles JF Fisac, E Bronstein, E Stefansson, D Sadigh, SS Sastry, AD Dragan 2019 International conference on robotics and automation (ICRA), 9590-9596 | 351 | 2019 |
| Dart: Noise injection for robust imitation learning M Laskey, J Lee, R Fox, A Dragan, K Goldberg Conference on robot learning, 143-156 | 329 | 2017 |
| Information gathering actions over human internal state D Sadigh, SS Sastry, SA Seshia, A Dragan 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 260 | 2016 |
| Planning for cars that coordinate with people: leveraging effects on human actions for planning and active information gathering over human internal state D Sadigh, N Landolfi, SS Sastry, SA Seshia, AD Dragan Autonomous Robots 42 (7), 1405-1426 | 253 | 2018 |
| Reward-rational (implicit) choice: A unifying formalism for reward learning HJ Jeon, S Milli, A Dragan Advances in Neural Information Processing Systems 33, 4415-4426 | 247 | 2020 |
| The social cost of strategic classification S Milli, J Miller, AD Dragan, M Hardt Proceedings of the conference on fairness, accountability, and transparency … | 245 | 2019 |
| Do you want your autonomous car to drive like you? C Basu, Q Yang, D Hungerman, M Singhal, AD Dragan Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot … | 242 | 2017 |
| Efficient iterative linear-quadratic approximations for nonlinear multi-player general-sum differential games D Fridovich-Keil, E Ratner, L Peters, AD Dragan, CJ Tomlin 2020 IEEE international conference on robotics and automation (ICRA), 1475-1481 | 241 | 2020 |
| Generating legible motion A Dragan, S Srinivasa Carnegie Mellon University | 241 | 2013 |
| Model reconstruction from model explanations S Milli, L Schmidt, AD Dragan, M Hardt Proceedings of the Conference on Fairness, Accountability, and Transparency, 1-9 | 240 | 2019 |
| The off-switch game D Hadfield-Menell, A Dragan, P Abbeel, S Russell IJCAI | 239 | 2017 |
| Shared autonomy via deep reinforcement learning S Reddy, AD Dragan, S Levine arXiv preprint arXiv:1802.01744 | 235 | 2018 |
| Automatically auditing large language models via discrete optimization E Jones, A Dragan, A Raghunathan, J Steinhardt International Conference on Machine Learning, 15307-15329 | 222 | 2023 |
| Gemma scope: Open sparse autoencoders everywhere all at once on gemma 2 T Lieberum, S Rajamanoharan, A Conmy, L Smith, N Sonnerat, V Varma, ... arXiv preprint arXiv:2408.05147 | 212 | 2024 |
| Enabling Robots to Communicate their Objectives SH Huang, D Held, P Abbeel, AD Dragan RSS | 207 | 2017 |
| Learning robot objectives from physical human interaction A Bajcsy, DP Losey, MK O’malley, AD Dragan Conference on robot learning, 217-226 | 202 | 2017 |
| Formalizing assistive teleoperation AD Dragan, SS Srinivasa Robotics: Science and Systems | 199 | 2012 |
| Probabilistically safe robot planning with confidence-based human predictions JF Fisac, A Bajcsy, SL Herbert, D Fridovich-Keil, S Wang, CJ Tomlin, ... arXiv preprint arXiv:1806.00109 | 178 | 2018 |
| Confidence-aware motion prediction for real-time collision avoidance1 D Fridovich-Keil, A Bajcsy, JF Fisac, SL Herbert, S Wang, AD Dragan, ... The International Journal of Robotics Research 39 (2-3), 250-265 | 177 | 2020 |
| Expressing robot incapability M Kwon, SH Huang, AD Dragan Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot … | 177 | 2018 |
| Establishing appropriate trust via critical states SH Huang, K Bhatia, P Abbeel, AD Dragan 2018 IEEE/RSJ international conference on intelligent robots and systems … | 172 | 2018 |
| Herb 2.0: Lessons learned from developing a mobile manipulator for the home SS Srinivasa, D Berenson, M Cakmak, A Collet, MR Dogar, AD Dragan, ... Proceedings of the IEEE 100 (8), 2410-2428 | 166 | 2012 |
| B-pref: Benchmarking preference-based reinforcement learning K Lee, L Smith, A Dragan, P Abbeel arXiv preprint arXiv:2111.03026 | 160 | 2021 |
| Physics-based grasp planning through clutter M Dogar, K Hsiao, M Ciocarlie, S Srinivasa MIT Press 8, 57-64 | 160 | 2012 |
| Deliberate delays during robot-to-human handovers improve compliance with gaze communication H Admoni, A Dragan, SS Srinivasa, B Scassellati Proceedings of the 2014 ACM/IEEE international conference on Human-robot … | 153 | 2014 |
| Where do you think you're going?: Inferring beliefs about dynamics from behavior S Reddy, A Dragan, S Levine Advances in Neural Information Processing Systems 31 | 139 | 2018 |
| Learning from physical human corrections, one feature at a time A Bajcsy, DP Losey, MK O'Malley, AD Dragan Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot … | 129 | 2018 |
| Managing ai risks in an era of rapid progress Y Bengio, G Hinton, A Yao, D Song, P Abbeel, YN Harari, YQ Zhang, ... arXiv preprint arXiv:2310.17688, 18 | 119 | 2023 |
| Pragmatic-pedagogic value alignment JF Fisac, MA Gates, JB Hamrick, C Liu, D Hadfield-Menell, ... Robotics research: the 18th international symposium Isrr, 49-57 | 111 | 2019 |
| Perceived robot capability E Cha, AD Dragan, SS Srinivasa 2015 24th IEEE International Symposium on Robot and Human Interactive … | 109 | 2015 |
| Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations M Laskey, J Lee, C Chuck, D Gealy, W Hsieh, FT Pokorny, AD Dragan, ... 2016 IEEE international conference on automation science and engineering … | 107 | 2016 |
| Shiv: Reducing supervisor burden in dagger using support vectors for efficient learning from demonstrations in high dimensional state spaces M Laskey, S Staszak, WYS Hsieh, J Mahler, FT Pokorny, AD Dragan, ... 2016 IEEE International Conference on Robotics and Automation (ICRA), 462-469 | 106 | 2016 |
| Courteous autonomous cars L Sun, W Zhan, M Tomizuka, AD Dragan 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 105 | 2018 |
| Integrating human observer inferences into robot motion planning A Dragan, S Srinivasa Autonomous Robots 37 (4), 351-368 | 105 | 2014 |
| Manipulation planning with goal sets using constrained trajectory optimization AD Dragan, ND Ratliff, SS Srinivasa 2011 IEEE International Conference on Robotics and Automation, 4582-4588 | 100 | 2011 |
| A scalable framework for real-time multi-robot, multi-human collision avoidance A Bajcsy, SL Herbert, D Fridovich-Keil, JF Fisac, S Deglurkar, AD Dragan, ... 2019 international conference on robotics and automation (ICRA), 936-943 | 99 | 2019 |
| Learning human objectives by evaluating hypothetical behavior S Reddy, A Dragan, S Levine, S Legg, J Leike International conference on machine learning, 8020-8029 | 98 | 2020 |
| Learning a prior over intent via meta-inverse reinforcement learning K Xu, E Ratner, A Dragan, S Levine, C Finn International conference on machine learning, 6952-6962 | 91 | 2019 |
| Legible robot pointing RM Holladay, AD Dragan, SS Srinivasa The 23rd IEEE International Symposium on robot and human interactive … | 91 | 2014 |
| Evaluating frontier models for dangerous capabilities M Phuong, M Aitchison, E Catt, S Cogan, A Kaskasoli, V Krakovna, ... arXiv preprint arXiv:2403.13793 | 90 | 2024 |
| Should Robots be Obedient? S Milli, D Hadfield-Menell, A Dragan, S Russell IJCAI | 89 | 2017 |
| Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations M Laskey, C Chuck, J Lee, J Mahler, S Krishnan, K Jamieson, A Dragan, ... ICRA | 87 | 2016 |
| On the feasibility of learning, rather than assuming, human biases for reward inference R Shah, N Gundotra, P Abbeel, A Dragan International conference on machine learning, 5670-5679 | 85 | 2019 |
| Goal inference improves objective and perceived performance in human-robot collaboration C Liu, JB Hamrick, JF Fisac, AD Dragan, JK Hedrick, SS Sastry, ... arXiv preprint arXiv:1802.01780 | 85 | 2018 |
| Benchmarks and algorithms for offline preference-based reward learning D Shin, AD Dragan, DS Brown arXiv preprint arXiv:2301.01392 | 84 | 2023 |
| Functional gradient motion planning in reproducing kernel hilbert spaces Z Marinho, A Dragan, A Byravan, B Boots, S Srinivasa, G Gordon arXiv preprint arXiv:1601.03648 | 79 | 2016 |
| Learning the communication of intent prior to physical collaboration K Strabala, MK Lee, A Dragan, J Forlizzi, SS Srinivasa 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human … | 78 | 2012 |
| Safety assurances for human-robot interaction via confidence-aware game-theoretic human models R Tian, L Sun, A Bajcsy, M Tomizuka, AD Dragan 2022 International Conference on Robotics and Automation (ICRA), 11229-11235 | 77 | 2022 |
| Preferences implicit in the state of the world R Shah, D Krasheninnikov, J Alexander, P Abbeel, A Dragan arXiv preprint arXiv:1902.04198 | 77 | 2019 |
| Movement primitives via optimization AD Dragan, K Muelling, JA Bagnell, SS Srinivasa 2015 IEEE International Conference on Robotics and Automation (ICRA), 2339-2346 | 76 | 2015 |
| Less is more: Rethinking probabilistic models of human behavior A Bobu, DRR Scobee, JF Fisac, SS Sastry, AD Dragan Proceedings of the 2020 acm/ieee international conference on human-robot … | 75 | 2020 |
| Expressive robot motion timing A Zhou, D Hadfield-Menell, A Nagabandi, AD Dragan Proceedings of the 2017 ACM/IEEE international conference on human-robot … | 74 | 2017 |
| Imagen 3 J Baldridge, J Bauer, M Bhutani, N Brichtova, A Bunner, L Castrejon, ... arXiv preprint arXiv:2408.07009 | 73 | 2024 |
| Engagement, user satisfaction, and the amplification of divisive content on social media S Milli, M Carroll, Y Wang, S Pandey, S Zhao, AD Dragan PNAS nexus 4 (3), pgaf062 | 72 | 2025 |
| Familiarization to robot motion A Dragan, S Srinivasa Proceedings of the 2014 ACM/IEEE international conference on Human-robot … | 71 | 2014 |
| Accelerating human learning with deep reinforcement learning S Reddy, S Levine, A Dragan NIPS workshop: teaching machines, robots, and humans 9, 5-9 | 70 | 2017 |
| Confronting reward model overoptimization with constrained rlhf T Moskovitz, AK Singh, DJ Strouse, T Sandholm, R Salakhutdinov, ... arXiv preprint arXiv:2310.04373 | 69 | 2023 |
| On the utility of model learning in hri R Choudhury, G Swamy, D Hadfield-Menell, AD Dragan 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI … | 69 | 2019 |
| Learning to model the world with language J Lin, Y Du, O Watkins, D Hafner, P Abbeel, D Klein, A Dragan arXiv preprint arXiv:2308.01399 | 68 | 2023 |
| Learning from richer human guidance: Augmenting comparison-based learning with feature queries C Basu, M Singhal, AD Dragan Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot … | 68 | 2018 |
| Causal confusion and reward misidentification in preference-based reward learning J Tien, JZY He, Z Erickson, AD Dragan, DS Brown arXiv preprint arXiv:2204.06601 | 66 | 2022 |
| Physical interaction as communication: Learning robot objectives online from human corrections DP Losey, A Bajcsy, MK O’Malley, AD Dragan The International Journal of Robotics Research 41 (1), 20-44 | 66 | 2022 |
| Estimating and penalizing induced preference shifts in recommender systems MD Carroll, A Dragan, S Russell, D Hadfield-Menell International Conference on Machine Learning, 2686-2708 | 63 | 2022 |
| Inferring rewards from language in context J Lin, D Fried, D Klein, A Dragan arXiv preprint arXiv:2204.02515 | 63 | 2022 |
| Feature expansive reward learning: Rethinking human input A Bobu, M Wiggert, C Tomlin, AD Dragan Proceedings of the 2021 ACM/IEEE international conference on human-robot … | 62 | 2021 |
| Scaled autonomy: Enabling human operators to control robot fleets G Swamy, S Reddy, S Levine, AD Dragan 2020 IEEE International Conference on Robotics and Automation (ICRA), 5942-5948 | 62 | 2020 |
| Translating Neuralese J Andreas, A Dragan, D Klein ACL | 61 | 2017 |
| The assistive multi-armed bandit L Chan, D Hadfield-Menell, S Srinivasa, A Dragan 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI … | 60 | 2019 |
| Teleoperation with intelligent and customizable interfaces AD Dragan, SS Srinivasa, KCT Lee Journal of Human-Robot Interaction 2 (2), 33-57 | 60 | 2013 |
| Value alignment verification DS Brown, J Schneider, A Dragan, S Niekum International Conference on Machine Learning, 1105-1115 | 59 | 2021 |
| Quantifying hypothesis space misspecification in learning from human–robot demonstrations and physical corrections A Bobu, A Bajcsy, JF Fisac, S Deglurkar, AD Dragan IEEE Transactions on Robotics 36 (3), 835-854 | 59 | 2020 |
| Learning from experience in manipulation planning: Setting the right goals AD Dragan, GJ Gordon, SS Srinivasa ISRR, 309-326 | 59* | 2012 |
| Ave: Assistance via empowerment Y Du, S Tiomkin, E Kiciman, D Polani, P Abbeel, A Dragan Advances in Neural Information Processing Systems 33, 4560-4571 | 55 | 2020 |
| Deceptive robot motion: synthesis, analysis and experiments A Dragan, R Holladay, S Srinivasa Autonomous Robots 39 (3), 331-345 | 55 | 2015 |
| An Analysis of Deceptive Robot Motion AD Dragan, R Holladay, SS Srinivasa Robotics Science and Systems | 55 | 2014 |
| Robot planning with mathematical models of human state and action AD Dragan arXiv preprint arXiv:1705.04226 | 52 | 2017 |
| Simplifying reward design through divide-and-conquer E Ratner, D Hadfield-Menell, AD Dragan arXiv preprint arXiv:1806.02501 | 50 | 2018 |
| Implicitly assisting humans to choose good grasps in robot to human handovers A Bestick, R Bajcsy, AD Dragan International symposium on experimental robotics, 341-354 | 48 | 2016 |
| The effect of modeling human rationality level on learning rewards from multiple feedback types GR Ghosal, M Zurek, DS Brown, AD Dragan Proceedings of the AAAI Conference on Artificial Intelligence 37 (5), 5983-5992 | 47 | 2023 |
| The boltzmann policy distribution: Accounting for systematic suboptimality in human models C Laidlaw, A Dragan arXiv preprint arXiv:2204.10759 | 47 | 2022 |
| Inducing structure in reward learning by learning features A Bobu, M Wiggert, C Tomlin, AD Dragan The International Journal of Robotics Research 41 (5), 497-518 | 47 | 2022 |
| A hamilton-jacobi reachability-based framework for predicting and analyzing human motion for safe planning S Bansal, A Bajcsy, E Ratner, AD Dragan, CJ Tomlin 2020 IEEE International Conference on Robotics and Automation (ICRA), 7149-7155 | 47 | 2020 |
| Generating plans that predict themselves JF Fisac, C Liu, JB Hamrick, S Sastry, JK Hedrick, TL Griffiths, AD Dragan Algorithmic Foundations of Robotics XII: Proceedings of the Twelfth Workshop … | 47 | 2020 |
| An efficient, generalized bellman update for cooperative inverse reinforcement learning D Malik, M Palaniappan, J Fisac, D Hadfield-Menell, S Russell, A Dragan International Conference on Machine Learning, 3394-3402 | 46 | 2018 |
| Learning human ergonomic preferences for handovers A Bestick, R Pandya, R Bajcsy, AD Dragan 2018 IEEE international conference on robotics and automation (ICRA), 3257-3264 | 46 | 2018 |
| Active comparison based learning incorporating user uncertainty and noise R Holladay, S Javdani, A Dragan, S Srinivasa RSS Workshop on Model Learning for Human-Robot Communication | 46 | 2016 |
| Viewpoint-based legibility optimization S Nikolaidis, A Dragan, S Srinivasa Human-Robot Interaction (HRI), 2016 11th ACM/IEEE International Conference … | 46* | 2016 |
| Evaluating the robustness of collaborative agents P Knott, M Carroll, S Devlin, K Ciosek, K Hofmann, AD Dragan, R Shah arXiv preprint arXiv:2101.05507 | 45 | 2021 |
| Learning under misspecified objective spaces A Bobu, A Bajcsy, JF Fisac, AD Dragan Conference on robot learning, 796-805 | 45 | 2018 |
| Uni [mask]: Unified inference in sequential decision problems M Carroll, O Paradise, J Lin, R Georgescu, M Sun, D Bignell, S Milani, ... Advances in neural information processing systems 35, 35365-35378 | 43 | 2022 |
| Benefits of assistance over reward learning R Shah, P Freire, N Alex, R Freedman, D Krasheninnikov, L Chan, ... | 40 | 2020 |
| Bridging rl theory and practice with the effective horizon C Laidlaw, SJ Russell, A Dragan Advances in Neural Information Processing Systems 36, 58953-59007 | 39 | 2023 |
| Goal representations for instruction following: A semi-supervised language interface to control V Myers, AW He, K Fang, HR Walke, P Hansen-Estruch, CA Cheng, ... Conference on Robot Learning, 3894-3908 | 39 | 2023 |
| Learning representations that enable generalization in assistive tasks JZY He, Z Erickson, DS Brown, A Raghunathan, A Dragan Conference on Robot Learning, 2105-2114 | 39 | 2023 |
| Situational confidence assistance for lifelong shared autonomy M Zurek, A Bobu, DS Brown, AD Dragan 2021 IEEE International Conference on Robotics and Automation (ICRA), 2783-2789 | 37 | 2021 |
| A robust control framework for human motion prediction A Bajcsy, S Bansal, E Ratner, CJ Tomlin, AD Dragan IEEE Robotics and Automation Letters 6 (1), 24-31 | 37 | 2020 |
| Inferring and assisting with constraints in shared autonomy N Mehr, R Horowitz, AD Dragan 2016 IEEE 55th Conference on Decision and Control (CDC), 6689-6696 | 36 | 2016 |
| Ai alignment with changing and influenceable reward functions M Carroll, D Foote, A Siththaranjan, S Russell, A Dragan arXiv preprint arXiv:2405.17713 | 35 | 2024 |
| Aligning robot and human representations A Bobu, A Peng, P Agrawal, J Shah, AD Dragan arXiv preprint arXiv:2302.01928 | 35 | 2023 |
| Learning to influence human behavior with offline reinforcement learning J Hong, S Levine, A Dragan Advances in neural information processing systems 36, 36094-36105 | 34 | 2023 |
| Twitter's algorithm: Amplifying anger, animosity, and affective polarization S Milli, M Carroll, S Pandey, Y Wang, AD Dragan CoRR | 34 | 2023 |
| Explainable robotic systems MMA De Graaf, BF Malle, A Dragan, T Ziemke Companion of the 2018 ACM/IEEE International Conference on Human-Robot … | 33 | 2018 |
| Zero-shot goal-directed dialogue via rl on imagined conversations J Hong, S Levine, A Dragan arXiv preprint arXiv:2311.05584 | 32 | 2023 |
| Human irrationality: both bad and good for reward inference L Chan, A Critch, A Dragan arXiv preprint arXiv:2111.06956 | 32 | 2021 |
| Policy gradient bayesian robust optimization for imitation learning Z Javed, DS Brown, S Sharma, J Zhu, A Balakrishna, M Petrik, A Dragan, ... International Conference on Machine Learning, 4785-4796 | 31 | 2021 |
| An approach to technical agi safety and security R Shah, A Irpan, AM Turner, A Wang, A Conmy, D Lindner, ... arXiv preprint arXiv:2504.01849 | 30 | 2025 |
| First contact: Unsupervised human-machine co-adaptation via mutual information maximization S Reddy, S Levine, A Dragan Advances in Neural Information Processing Systems 35, 31542-31556 | 30 | 2022 |
| Estimating and penalizing preference shift in recommender systems M Carroll, D Hadfield-Menell, S Russell, A Dragan Proceedings of the 15th ACM Conference on Recommender Systems, 661-667 | 30 | 2021 |
| Aligning human and robot representations A Bobu, A Peng, P Agrawal, JA Shah, AD Dragan Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot … | 29 | 2024 |
| Towards modeling and influencing the dynamics of human learning R Tian, M Tomizuka, AD Dragan, A Bajcsy Proceedings of the 2023 ACM/IEEE international conference on human-robot … | 29 | 2023 |
| On the sensitivity of reward inference to misspecified human models J Hong, K Bhatia, A Dragan arXiv preprint arXiv:2212.04717 | 29 | 2022 |
| Analyzing human models that adapt online A Bajcsy, A Siththaranjan, CJ Tomlin, AD Dragan 2021 IEEE International Conference on Robotics and Automation (ICRA), 2754-2760 | 29 | 2021 |
| Optimal cost design for model predictive control A Jain, L Chan, DS Brown, AD Dragan Learning for Dynamics and Control, 1205-1217 | 29 | 2021 |
| Variational Bayesian optimization for runtime risk-sensitive control S Kuindersma, R Grupen, A Barto Robotics: Science and systems viii, 201-208 | 29 | 2012 |
| Sirl: Similarity-based implicit representation learning A Bobu, Y Liu, R Shah, DS Brown, AD Dragan Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot … | 28 | 2023 |
| Control for Societal-Scale Challenges: Roadmap 2030 A Alleyne, F Allgöwer, AD Ames, S Amin, J Anderson, AM Annaswamy, ... IEEE Control Systems Society Publication | 28 | 2023 |
| The MineRL BASALT competition on learning from human feedback R Shah, C Wild, SH Wang, N Alex, B Houghton, W Guss, S Mohanty, ... arXiv preprint arXiv:2107.01969 | 28 | 2021 |
| Exploiting passive dynamics with variable stiffness actuation in robot brachiation J Nakanishi, S Vijayakumar Robotics: Science and systems 8, 305 | 28 | 2013 |
| On targeted manipulation and deception when optimizing llms for user feedback M Williams, M Carroll, A Narang, C Weisser, B Murphy, A Dragan arXiv preprint arXiv:2411.02306 | 27 | 2024 |
| Learning temporal distances: Contrastive successor features can provide a metric structure for decision-making V Myers, C Zheng, A Dragan, S Levine, B Eysenbach arXiv preprint arXiv:2406.17098 | 27 | 2024 |
| Asha: Assistive teleoperation via human-in-the-loop reinforcement learning S Chen, J Gao, S Reddy, G Berseth, AD Dragan, S Levine 2022 International Conference on Robotics and Automation (ICRA), 7505-7512 | 26 | 2022 |
| Literal or pedagogic human? analyzing human model misspecification in objective learning S Milli, AD Dragan Uncertainty in artificial intelligence, 925-934 | 26 | 2020 |
| Cost functions for robot motion style A Zhou, AD Dragan 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 26 | 2018 |
| Special issue on learning for human–robot collaboration L Rozo, HB Amor, S Calinon, A Dragan, D Lee Autonomous Robots 42 (5), 953-956 | 26 | 2018 |
| Online customization of teleoperation interfaces AD Dragan, SS Srinivasa 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human … | 26 | 2012 |
| Toward grounded commonsense reasoning M Kwon, H Hu, V Myers, S Karamcheti, A Dragan, D Sadigh 2024 IEEE International Conference on Robotics and Automation (ICRA), 5463-5470 | 25 | 2024 |
| Offline preference-based apprenticeship learning D Shin, DS Brown, AD Dragan arXiv preprint arXiv:2107.09251 | 24 | 2021 |
| On complementing end-to-end human behavior predictors with planning L Sun, X Jia, AD Dragan arXiv preprint arXiv:2103.05661 | 23 | 2021 |
| Choice set misspecification in reward inference R Freedman, R Shah, A Dragan arXiv preprint arXiv:2101.07691 | 23 | 2021 |
| Legible robot motion planning AD Dragan Carnegie Mellon University | 23 | 2015 |
| Chain of thought monitorability: A new and fragile opportunity for ai safety T Korbak, M Balesni, E Barnes, Y Bengio, J Benton, J Bloom, M Chen, ... arXiv preprint arXiv:2507.11473 | 21 | 2025 |
| Assisted perception: optimizing observations to communicate state S Reddy, S Levine, A Dragan Conference on robot learning, 748-764 | 21 | 2021 |
| Nonverbal robot feedback for human teachers SH Huang, I Huang, R Pandya, AD Dragan arXiv preprint arXiv:1911.02320 | 21 | 2019 |
| Assitive Teleoperation for Manipulation Tasks AD Dragan, SS Srinivasa | 20 | 2012 |
| Preventing reward hacking with occupancy measure regularization C Laidlaw, S Singhal, A Dragan | 18 | 2023 |
| Toward grounded social reasoning M Kwon, H Hu, V Myers, S Karamcheti, A Dragan, D Sadigh arXiv preprint arXiv:2306.08651 | 18 | 2023 |
| Pragmatic image compression for human-in-the-loop decision-making S Reddy, A Dragan, S Levine Advances in Neural Information Processing Systems 34, 26499-26510 | 18 | 2021 |
| Adversaries can misuse combinations of safe models E Jones, A Dragan, J Steinhardt arXiv preprint arXiv:2406.14595 | 17 | 2024 |
| Correlated proxies: A new definition and improved mitigation for reward hacking C Laidlaw, S Singhal, A Dragan arXiv preprint arXiv:2403.03185 | 17 | 2024 |
| Optimal behavior prior: Data-efficient human models for improved human-ai collaboration M Yang, M Carroll, A Dragan arXiv preprint arXiv:2211.01602 | 17 | 2022 |
| Teaching robots to span the space of functional expressive motion A Sripathy, A Bobu, Z Li, K Sreenath, DS Brown, AD Dragan 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 17 | 2022 |
| Preference learning along multiple criteria: A game-theoretic perspective K Bhatia, A Pananjady, P Bartlett, A Dragan, MJ Wainwright Advances in neural information processing systems 33, 7413-7424 | 17 | 2020 |
| Learning from extrapolated corrections JY Zhang, AD Dragan 2019 International Conference on Robotics and Automation (ICRA), 7034-7040 | 17 | 2019 |
| Social cohesion in autonomous driving NC Landolfi, AD Dragan 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 17 | 2018 |
| Assisted robust reward design JZY He, AD Dragan arXiv preprint arXiv:2111.09884 | 16 | 2021 |
| How to be helpful to multiple people at once V Gates, TL Griffiths, AD Dragan Cognitive science 44 (6), e12841 | 16 | 2020 |
| Learning optimal advantage from preferences and mistaking it for reward WB Knox, S Hatgis-Kessell, SO Adalgeirsson, S Booth, A Dragan, P Stone, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (9), 10066 … | 15 | 2024 |
| A study of causal confusion in preference-based reward learning J Tien, JZY He, Z Erickson, A Dragan, DS Brown ICML 2022: Workshop on Spurious Correlations, Invariance and Stability | 15 | 2022 |
| Human-AI learning performance in multi-armed bandits R Pandya, SH Huang, D Hadfield-Menell, AD Dragan Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 369-375 | 15 | 2019 |
| Trajectory improvement and reward learning from comparative language feedback Z Yang, M Jun, J Tien, SJ Russell, A Dragan, E Bıyık arXiv preprint arXiv:2410.06401 | 14 | 2024 |
| Explaining robot policies O Watkins, S Huang, J Frost, K Bhatia, E Weiner, P Abbeel, T Darrell, ... Applied AI Letters 2 (4), e52 | 13 | 2021 |
| Experiments with Balancing on Irregular Terrains using the Dreamer Mobile Humanoid Robot. L Sentis, J Petersen, R Philippsen Robotics: Science and Systems | 13 | 2012 |
| Introduction to the special issue on explainable robotic systems MMA De Graaf, A Dragan, BF Malle, T Ziemke ACM Transactions on Human-Robot Interaction (THRI) 10 (3), 1-4 | 12 | 2021 |
| X2T: Training an x-to-text typing interface with online learning from user feedback J Gao, S Reddy, G Berseth, N Hardy, N Natraj, K Ganguly, AD Dragan, ... arXiv preprint arXiv:2203.02072 | 11 | 2022 |
| Effects of robot capability on user acceptance E Cha, AD Dragan, SS Srinivasa 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI … | 11 | 2013 |
| Cos: Enhancing personalization and mitigating bias with context steering JZY He, S Pandey, ML Schrum, A Dragan arXiv preprint arXiv:2405.01768 | 10 | 2024 |
| Dynamically switching human prediction models for efficient planning A Sripathy, A Bobu, DS Brown, AD Dragan 2021 IEEE International Conference on Robotics and Automation (ICRA), 3495-3501 | 10 | 2021 |
| Bayesian robustness: A nonasymptotic viewpoint K Bhatia, YA Ma, AD Dragan, PL Bartlett, MI Jordan arXiv preprint arXiv:1907.11826 | 10 | 2019 |
| Feature-based prediction of trajectories for socially compliant navigation P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 10 | 2013 |
| When your ais deceive you: Challenges with partial observability of human evaluators in reward learning L Lang, D Foote, S Russell, AD Dragan, E Jenner, S Emmons CoRR | 9 | 2024 |
| Configuration space metrics HJ Jeon, AD Dragan 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 9 | 2018 |
| Collaborative manipulation: new challenges for robotics and hri AD Dragan, AL Thomaz, SS Srinivasa 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI … | 9 | 2013 |
| Distributed Approximation of Joint Measurement Distributions Using Mixtures of Gaussians. BJ Julian, SL Smith, D Rus Robotics: Science and Systems | 9 | 2012 |
| Q-sft: Q-learning for language models via supervised fine-tuning J Hong, A Dragan, S Levine arXiv preprint arXiv:2411.05193 | 8 | 2024 |
| Towards flexible inference in sequential decision problems via bidirectional transformers M Carroll, J Lin, O Paradise, R Georgescu, M Sun, D Bignell, S Milani, ... arXiv preprint arXiv:2204.13326 | 8 | 2022 |
| Learning what to do by simulating the past D Lindner, R Shah, P Abbeel, A Dragan arXiv preprint arXiv:2104.03946 | 8 | 2021 |
| Learning to assist humans without inferring rewards V Myers, E Ellis, S Levine, B Eysenbach, A Dragan Advances in Neural Information Processing Systems 37, 71540-71567 | 7 | 2024 |
| Offline rl with observation histories: Analyzing and improving sample complexity J Hong, A Dragan, S Levine arXiv preprint arXiv:2310.20663 | 7 | 2023 |
| Time-efficient reward learning via visually assisted cluster ranking D Zhang, M Carroll, A Bobu, A Dragan arXiv preprint arXiv:2212.00169 | 7 | 2022 |
| On complementing end-to-end human motion predictors with planning L Sun, X Jia, AD Dragan 2021 Robotics: Science and Systems (RSS) | 7 | 2021 |
| Effects of speech on perceived capability E Cha, A Dragan, J Forlizzi, S Srinivasa Proceedings of the 2014 ACM/IEEE international conference on Human-robot … | 7 | 2014 |
| When your AIs deceive you: Challenges of partial observability in reinforcement learning from human feedback L Lang, D Foote, SJ Russell, A Dragan, E Jenner, S Emmons Advances in Neural Information Processing Systems 37, 93240-93299 | 6 | 2024 |
| A generalized acquisition function for preference-based reward learning E Ellis, GR Ghosal, SJ Russell, A Dragan, E Bıyık 2024 IEEE International Conference on Robotics and Automation (ICRA), 2814-2821 | 6 | 2024 |
| The Effective Horizon Explains Deep RL Performance in Stochastic Environments C Laidlaw, B Zhu, S Russell, A Dragan arXiv preprint arXiv:2312.08369 | 6 | 2023 |
| Efficient cooperative inverse reinforcement learning M Palaniappan, D Malik, D Hadfield-Menell, A Dragan, S Russell Proc. ICML Workshop on Reliable Machine Learning in the Wild | 6 | 2017 |
| Bayesian robustness: A nonasymptotic viewpoint K Bhatia, YA Ma, AD Dragan, PL Bartlett, MI Jordan Journal of the American Statistical Association 119 (546), 1112-1123 | 5 | 2024 |
| Scalably solving assistance games C Laidlaw, E Bronstein, T Guo, D Feng, L Berglund, J Svegliato, S Russell, ... ICLR 2025 Workshop on Bidirectional Human-AI Alignment | 5 | 2024 |
| Defining deception in decision making M Abdulhai, M Carroll, J Svegliato, A Shrivastava, A Dragan, S Levine | 4 | 2024 |
| Context steering: Controllable personalization at inference time JZY He, S Pandey, ML Schrum, A Dragan arXiv preprint arXiv:2405.01768 | 4 | 2024 |
| Optimizing robot behavior via comparative language feedback J Tien, Z Yang, M Jun, SJ Russell, A Dragan, E Bıyık Proceedings of the 16th International Conference on Social Robotics (ICSR … | 4 | 2024 |
| Contextual reliability: When different features matter in different contexts GR Ghosal, A Setlur, DS Brown, A Dragan, A Raghunathan International Conference on Machine Learning, 11300-11320 | 4 | 2023 |
| On the utility of model learning in hri G Swamy, J Schulz, R Choudhury, D Hadfield-Menell, A Dragan arXiv preprint arXiv:1901.01291 | 4 | 2019 |
| Temporal Representation Alignment: Successor Features Enable Emergent Compositionality in Robot Instruction Following V Myers, BC Zheng, A Dragan, K Fang, S Levine arXiv preprint arXiv:2502.05454 | 3 | 2025 |
| Interactive dialogue agents via reinforcement learning on hindsight regenerations J Hong, J Lin, A Dragan, S Levine arXiv preprint arXiv:2411.05194 | 3 | 2024 |
| Efficient Dynamics Estimation With Adaptive Model Sets E Ratner, A Bajcsy, T Fong, CJ Tomlin, AD Dragan IEEE robotics and automation letters 6 (2), 2373-2380 | 3 | 2021 |
| Leveraging critical states to develop trust SH Huang, K Bhatia, P Abbeel, AD Dragan RSS 2017 Workshop: Morality and Social Trust in Autonomous Robots | 3 | 2017 |
| Pre-school children's first encounter with a robot E Cha, A Dragan, S Srinivasa Proceedings of the 2014 ACM/IEEE international conference on Human-robot … | 3 | 2014 |
| Extrinsic calibration from per-sensor egomotion P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 3 | 2013 |
| Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation M Pan, M Schrum, V Myers, E Bıyık, A Dragan arXiv preprint arXiv:2406.06714 | 2 | 2024 |
| Scalable oversight by accounting for unreliable feedback S Singhal, C Laidlaw, A Dragan ICML 2024 Workshop on Models of Human Feedback for AI Alignment | 2 | 2024 |
| Bootstrapping Adaptive Human-Machine Interfaces with Offline Reinforcement Learning J Gao, S Reddy, G Berseth, AD Dragan, S Levine 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 2 | 2023 |
| Video-guided skill discovery M Tomar, D Ghosh, V Myers, A Dragan, ME Taylor, P Bachman, S Levine ICML 2023 Workshop The Many Facets of Preference-Based Learning | 2 | 2023 |
| Agnostic learning with unknown utilities K Bhatia, PL Bartlett, AD Dragan, J Steinhardt arXiv preprint arXiv:2104.08482 | 2 | 2021 |
| Irrationality can help reward inference L Chan, A Critch, A Dragan | 2 | 2019 |
| Few-shot intent inference via meta-inverse reinforcement learning K Xu, E Ratner, A Dragan, S Levine, C Finn | 2 | 2018 |
| Inferring reward functions from demonstrators with unknown biases R Shah, N Gundotra, P Abbeel, A Dragan | 2 | 2018 |
| Assistive teleoperation: A new domain for interactive learning A Dragan, S Srinivasa AAAI fall symposium on robots interactively learning from human teachers, 1-4 | 2 | 2012 |
| AssistanceZero: Scalably Solving Assistance Games C Laidlaw, E Bronstein, T Guo, D Feng, L Berglund, J Svegliato, S Russell, ... arXiv preprint arXiv:2504.07091 | 1 | 2025 |
| Cos: Enhancing personalization and mitigating bias with context steering S Pandey, JZY He, ML Schrum, A Dragan Neurips Safe Generative AI Workshop 2024 | 1 | 2024 |
| Quantifying Assistive Robustness Via the Natural-Adversarial Frontier JZY He, DS Brown, Z Erickson, A Dragan Conference on Robot Learning, 1865-1886 | 1 | 2023 |
| Engagement, User Satisfaction, and the Amplification of Divisive Content on Social Media Emilie Flamme S Milli, M Carroll, Y Wang, S Pandey, S Zhao, A Dragan | 1 | 2023 |
| Enabling Generalization of Human Models for Human-AI Collaboration to New Tasks X Yang, A Dragan Master’s thesis. EECS Department, University of California, Berkeley. http … | 1 | 2021 |
| Xt2: Training an x-to-text typing interface with online learning from implicit feedback J Gao, S Reddy, G Berseth, AD Dragan, S Levine International Conference on Learning Representations (ICLR) | 1 | 2021 |
| An extensible interactive interface for agent design M Rahtz, J Fang, AD Dragan, D Hadfield-Menell arXiv preprint arXiv:1906.02641 | 1 | 2019 |
| Specifying AI Objectives as a Human-AI Collaboration problem A Dragan Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 329-329 | 1 | 2019 |
| Towards Persistent Localization and Mapping with a Continuous Appearance-Based Topology P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 1 | 2013 |
| Parsing Indoor Scenes Using RGB-D Imager P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 1 | 2013 |
| Recognition, Prediction, and Planning for Assisted Teleoperation of Freeform Tasks P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 1 | 2013 |
| Learning to provide better examples for our robots A Dragan, S Srinivasa Carnegie Mellon University | 1 | 2011 |
| A Theoretical Explanation of Deep RL Performance in Stochastic Environments C Laidlaw, B Zhu, S Russell, A Dragan NeurIPS 2023 Workshop on Generalization in Planning | 1 | |
| The impacts of known and unknown demonstrator irrationality on reward inference L Chan, A Critch, A Dragan | 1 | |
| What Would pi* Do?: Imitation Learning via Off-Policy Reinforcement Learning S Reddy, AD Dragan, S Levine | 1 | |
| Can AI Mediation Improve Democratic Deliberation? Sébastien A. Krier using Midjourney 6.1 MH Tessler, G Evans, MA Bakker, I Gabriel, S Bridgers, R Jain, R Koster, ... Artificial Intelligence | | 2025 |
| Planning without Search: Refining Frontier LLMs with Offline Goal-Conditioned RL J Hong, A Dragan, S Levine arXiv preprint arXiv:2505.18098 | | 2025 |
| Achieving AI Alignment with Unreliable Supervision S Singhal, C Laidlaw, A Dragan | | 2024 |
| Preventing Reward Hacking with Occupancy Measure Regularization S Singhal, C Laidlaw, A Dragan | | 2024 |
| Context Steering: Controllable Personalization at Inference Time J Zhi-Yang He, S Pandey, ML Schrum, A Dragan arXiv e-prints, arXiv: 2405.01768 | | 2024 |
| Quantifying Assistive Robustness Via the Natural-Adversarial Frontier J Zhi-Yang He, Z Erickson, DS Brown, AD Dragan arXiv e-prints, arXiv: 2310.10610 | | 2023 |
| Collaborative Research: HCC: Medium: Aligning Robot Representations with Humans A Dragan NSF Award Number 2310757. Directorate for Computer and Information Science … | | 2023 |
| Similarity-Based Representation Learning Y Liu, A Bobu, A Dragan | | 2023 |
| Learning Representations that Enable Generalization in Assistive Tasks J Zhi-Yang He, A Raghunathan, DS Brown, Z Erickson, AD Dragan arXiv e-prints, arXiv: 2212.03175 | | 2022 |
| Implicit Communication in Human-Machine Collaboration A Dragan | | 2022 |
| Inducing Structure in Reward Learning by Learning A Bobu, M Wiggert, C Tomlin, A Dragan | | 2021 |
| Assisted Robust Reward Design J Zhi-Yang He, AD Dragan arXiv e-prints, arXiv: 2111.09884 | | 2021 |
| Analyzing Human Models that Adapt Online A Sripathy, A Bobu, D Brown, A Dragan IEEE International Conference on Robotics and Automation | | 2021 |
| Explainable Robotic Systems: Introduction to the special issue M DE GRAAF, A DRAGAN, BF MALLE, TOM ZIEMKE | | 2021 |
| Project Plan: Benchmarking Representation Learning for Imitation Learning X Chen, S Toyer, C Wild, N Alex, BS Emmons, S Wang, S Russell, ... | | 2020 |
| Learning with Humans in the Loop G Swamy, A Dragan, S Levine | | 2020 |
| Comparing Game Planners S Luo, A Dragan | | 2020 |
| Learning from Intended Corrections JY Zhang, AD Dragan CoRR | | 2018 |
| The Off-Switch Game: Incentives for Allowing AI Shutdown D Hadfield-Menell, A Dragan, P Abbeel, S Russell < bound method Organization. get_name_with_acronym of< Organization … | | 2017 |
| CAREER: Towards Autonomously Generating Robot Behavior for Coordination with Humans-Accounting for Effects on Human Actions A Dragan NSF Award Number 1652083. Directorate for Computer and Information Science … | | 2017 |
| Geometric Mechanics for Continuous Swimmers on Granular Material J Dai, H Faraji, P Schiebel, C Gong, M Travers, R Hatton, D Goldman, ... APS March Meeting Abstracts 2016, V40. 004 | | 2016 |
| Publication Submission Form TW Fong, J Scholtz, J Shah, L Flueckiger, C Kunz, D Lees, J Schreiner, ... Journal Article 30 (3), 705-718 | | 2014 |
| Legible user input for intent prediction KCT Lee, AD Dragan, SS Srinivasa 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI … | | 2013 |
| Distributed Approximation of Joint Measurement Distributions Using Mixtures of Gaussians P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Visual Route Recognition with a Handful of Bits P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Contextual Sequence Prediction with Application to Control Library Optimization P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Failure Anticipation in Pursuit-Evasion P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Real-Time Inverse Dynamics Learning for Musculoskeletal Robots Based on Echo State Gaussian Process Regression P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| What's in the Bag: A Distributed Approach to 3D Shape Duplication with Modular Robots P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| E-Graphs: Bootstrapping Planning with Experience Graphs P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Optimal Control with Weighted Average Costs and Temporal Logic Specifications P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Towards A Swarm of Agile Micro Quadrotors P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Efficiently Finding Optimal Winding-Constrained Loops in the Plane P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Affine Trajectory Deformation for Redundant Manipulators P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Hierarchical Motion Planning in Topological Representations P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Reducing Conservativeness in Safety Guarantees by Learning Disturbances Online: Iterated Guaranteed Safe Online Learning P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Probabilistic Temporal Logic for Motion Planning with Resource Threshold Constraints P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Time-Optimal Trajectory Generation for Path Following with Bounded Acceleration and Velocity P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Nonparametric Bayesian Models for Unsupervised Scene Analysis and Reconstruction P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Minimal Coordinate Formulation of Contact Dynamics in Operational Space P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Inference on Networks of Mixtures for Robust Robot Mapping P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Robust Object Grasping Using Force Compliant Motion Primitives P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| FFT-Based Terrain Segmentation for Underwater Mapping P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Robust Navigation Execution by Planning in Belief Space P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Development of a Testbed for Robotic Neuromuscular Controllers P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | | 2013 |
| Publication Submission Form TD Niemueller, G Lakemeyer, S Srinivasa, D Berenson, M Cakmak, ... Journal Article 100 (8), 2410-2428 | | 2012 |
| The Effective Horizon Challenge C Laidlaw, D Khalil, M Li, L Newhouse, S Russell, A Dragan The Exploration in AI Today Workshop at ICML 2025 | | |
| CTRL-Rec: Controlling Recommender Systems With Natural Language M Carroll, A Foote, M Williams, A Dragan, WB Knox, S Milli ICLR 2025 Workshop on Bidirectional Human-AI Alignment | | |
| Diagnostic Uncertainty: Teaching Language Models to Describe Open-Ended Uncertainty B Sui, J Lin, M Li, A Dragan, D Klein, J Steinhardt ICLR 2025 Workshop on Building Trust in Language Models and Applications | | |
| Zero-Shot Goal Dialogue via Reinforcement Learning on Imagined Conversations J Hong, S Levine, A Dragan | | |
| Reliability-Aware Preference Learning for LLM Reward Models S Singhal, C Laidlaw, A Dragan | | |
| Targeted Manipulation and Deception Emerge in LLMs Trained on User* Feedback M Williams, M Carroll, C Weisser, B Murphy, A Narang, A Dragan Workshop on Socially Responsible Language Modelling Research | | |
| Successor Representations Enable Emergent Compositional Instruction Following V Myers, C Zheng, A Dragan, K Fang, S Levine | | |
| CoS: Enhancing Personalization with Context Steering S Pandey, JZY He, ML Schrum, A Dragan Workshop on Socially Responsible Language Modelling Research | | |
| Learning human-robot collaboration from human feedback JZY He, A Rai, AD Dragan | | |
| RobULA: Efficient Sampling for Robust Bayesian Inference K Bhatia, YA Ma, AD Dragan, MI Jordan, PL Bartlett | | |
| Model-Free Shared Autonomy through Deep Human-in-the-Loop Reinforcement Learning S Reddy, A Dragan, S Levine | | |
| Publication Submission Form ZAM Marinho, AFT Martins, SB Cohen, NA Smit, A Dragan, A Byravan, ... | | |
| Scalable Confidence-Aware Safety Analysis for Robot Planning around Multiple Humans JF Fisac, D Fridovich-Keil, A Bajcsy, S Herbert, S Deglurkar, C Tomlin, ... | | |
| Collaborators: Dorsa Sadigh, Chandrayee Basu, Sanjit Seshia A Dragan | | |
| Report: Verifiable Control for (Semi) Autonomous Cars that Learns from Human (Re) Actions A Dragan, SS Sastry, SA Seshia | | |
| Planning with Observable Operator Models Guided Research Final Report A Dragan | | |
| Trajectory Optimization for Predictable and Legible Motion AD Dragan, SS Srinivasa | | |
.jpg/1920px-Nyctanthes_arbor-tristis_L._(3228498390).jpg?_=20160920203037)
_flower_at_Madhurawada_01.JPG/1920px-(Nyctanthes_arbor-tristis)_flower_at_Madhurawada_01.JPG?_=20121208060344)
.jpg/1379px-Capercaillie_(8751340764).jpg)
Posts
