Do Feature Attribution Methods Correctly Attribute Features? Y Zhou, S Booth, MT Ribeiro, J Shah Proceedings of the AAAI Conference on Artificial Intelligence, 2022 | 130 | 2022 |
Piggybacking robots: Human-robot overtrust in university dormitory security S Booth, J Tompkin, H Pfister, J Waldo, K Gajos, R Nagpal Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot …, 2017 | 104 | 2017 |
IEEE P7001: A proposed standard on transparency AFT Winfield, S Booth, LA Dennis, T Egawa, H Hastie, N Jacobs, ... Frontiers in Robotics and AI 8, 665729, 2021 | 83 | 2021 |
Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development A Hopkins*, S Booth* Proceedings of the 2021 AAAI/ACM Conferenceon AI, Ethics, and Society (AIES ’21), 2021 | 46 | 2021 |
The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications S Booth, WB Knox, J Shah, S Niekum, P Stone, A Allievi Proceedings of the AAAI Conference on Artificial Intelligence, 2023 | 40 | 2023 |
Virtual, Augmented, and Mixed Reality for Human-Robot Interaction (VAM-HRI) T Williams, D Szafir, T Chakraborti, OS Khim, E Rosen, S Booth, ... HRI '20: Companion of the 2020 ACM/IEEE International Conference on Human …, 2020 | 33 | 2020 |
Bayes-TrEx: A Bayesian Sampling Approach to Model Transparency by Example S Booth*, Y Zhou*, A Shah, J Shah Proceedings of the AAAI Conference on Artificial Intelligence, 2021 | 28* | 2021 |
Models of human preference for learning reward functions WB Knox, S Hatgis-Kessell, S Booth, S Niekum, P Stone, A Allievi https://arxiv.org/abs/2206.02231, 2022 | 25 | 2022 |
Evaluating the Interpretability of the Knowledge Compilation Map: Communicating Logical Statements Effectively S Booth, C Muise, J Shah Proceedings of the Twenty-Eighth International Joint Conference on …, 2019 | 22 | 2019 |
Revisiting Human-Robot Teaching and Learning Through the Lens of Human Concept Learning S Booth, S Sharma, S Chung, J Shah, EL Glassman ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2022 | 21 | 2022 |
The irrationality of neural rationale models Y Zheng, S Booth, J Shah, Y Zhou arXiv preprint arXiv:2110.07550, 2021 | 18 | 2021 |
RoCUS: Robot Controller Understanding via Sampling Y Zhou, S Booth, N Figueroa, J Shah Conference on Robot Learning, 2021 | 14 | 2021 |
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 …, 2024 | 5 | 2024 |
Variable autonomy for human-robot teaming (vat) M Chiou, S Booth, B Lacerda, A Theodorou, S Rothfuß Companion of the 2023 ACM/IEEE international conference on human-robot …, 2023 | 5 | 2023 |
Varying How We Teach: Adding Contrast Helps Humans Learn about Robot Motions T Horter, E Glassman, J Shah, S Booth HRI Human-Interactive Robot Learning Workshop, 2023 | 2 | 2023 |
Modeling Blackbox Agent Behaviour via Knowledge Compilation C Muise, S Wollenstein-Betech, S Booth, J Shah, Y Khazaen AAAI Workshop on Plan, Activity, and Intent Recognition (PAIR), 2020 | 2 | 2020 |
Explainable AI foundations to support human-robot teaching and learning SL Booth Massachusetts Institute of Technology, 2020 | 2 | 2020 |
Quality-Diversity Generative Sampling for Learning with Synthetic Data A Chang, MC Fontaine, S Booth, MJ Matarić, S Nikolaidis AAAI Conference on Artificial Intelligence, 2024 | 1 | 2024 |
Building Blocks for Human-AI Alignment: Specify, Inspect, Model, and Revise SL Booth Massachusetts Institute of Technology, 2024 | | 2024 |
Aligning Robot Behaviors with Human Intents by Exposing Learned Behaviors and Resolving Misspecifications S Booth HRI Pioneers, 2023 | | 2023 |