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2020 – today
- 2024
[b1]Serena Booth:
Building Blocks for Human-AI Alignment: Specify, Inspect, Model, and Revise. MIT, USA, 2024- [j2]W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, Alessandro Gabriele Allievi:
Models of human preference for learning reward functions. Trans. Mach. Learn. Res. 2024 (2024) - [c13]W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur O. Adalgeirsson, Serena Booth, Anca D. Dragan, Peter Stone, Scott Niekum:
Learning Optimal Advantage from Preferences and Mistaking It for Reward. AAAI 2024: 10066-10073 - [c12]Allen Chang, Matthew C. Fontaine, Serena Booth, Maja J. Mataric, Stefanos Nikolaidis:
Quality-Diversity Generative Sampling for Learning with Synthetic Data. AAAI 2024: 19805-19812 - 2023
- [c11]Serena Booth, W. Bradley Knox, Julie Shah, Scott Niekum, Peter Stone, Alessandro Allievi:
The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications. AAAI 2023: 5920-5929 - [c10]Serena Booth
:
Aligning Robot Behaviors with Human Intents by Exposing Learned Behaviors and Resolving Misspecifications. HRI (Companion) 2023: 742-744 - [c9]Manolis Chiou, Serena Booth, Bruno Lacerda, Andreas Theodorou, Simon Rothfuß:
Variable Autonomy for Human-Robot Teaming (VAT). HRI (Companion) 2023: 932-934 - [i9]W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur O. Adalgeirsson, Serena Booth, Anca D. Dragan, Peter Stone, Scott Niekum:
Learning Optimal Advantage from Preferences and Mistaking it for Reward. CoRR abs/2310.02456 (2023) - [i8]Allen Chang, Matthew C. Fontaine, Serena Booth, Maja J. Mataric, Stefanos Nikolaidis:
Quality-Diversity Generative Sampling for Learning with Synthetic Data. CoRR abs/2312.14369 (2023) - 2022
- [c8]Yilun Zhou, Serena Booth, Marco Túlio Ribeiro, Julie Shah:
Do Feature Attribution Methods Correctly Attribute Features? AAAI 2022: 9623-9633 - [c7]Serena Booth, Sanjana Sharma, Sarah Chung, Julie Shah, Elena L. Glassman:
Revisiting Human-Robot Teaching and Learning Through the Lens of Human Concept Learning. HRI 2022: 147-156 - [i7]W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, Alessandro Allievi:
Models of human preference for learning reward functions. CoRR abs/2206.02231 (2022) - 2021
- [j1]Alan F. T. Winfield, Serena Booth, Louise A. Dennis, Takashi Egawa, Helen F. Hastie, Naomi Jacobs, Roderick I. Muttram, Joanna I. Olszewska, Fahimeh Rajabiyazdi, Andreas Theodorou, Mark A. Underwood, Robert H. Wortham, Eleanor Nell Watson:
IEEE P7001: A Proposed Standard on Transparency. Frontiers Robotics AI 8: 665729 (2021) - [c6]Serena Booth, Yilun Zhou, Ankit Shah, Julie Shah:
Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example. AAAI 2021: 11423-11432 - [c5]Aspen K. Hopkins, Serena Booth:
Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development. AIES 2021: 134-145 - [c4]Yilun Zhou, Serena Booth, Nadia Figueroa, Julie Shah:
RoCUS: Robot Controller Understanding via Sampling. CoRL 2021: 850-860 - [i6]Yilun Zhou, Serena Booth, Marco Túlio Ribeiro, Julie Shah:
Do Feature Attribution Methods Correctly Attribute Features? CoRR abs/2104.14403 (2021) - [i5]Aspen K. Hopkins, Serena Booth:
Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development. CoRR abs/2110.02932 (2021) - [i4]Yiming Zheng, Serena Booth, Julie Shah, Yilun Zhou:
The Irrationality of Neural Rationale Models. CoRR abs/2110.07550 (2021) - 2020
- [c3]Tom Williams, Daniel Szafir, Tathagata Chakraborti, Soh-Khim Ong, Eric Rosen, Serena Booth, Thomas R. Groechel:
Virtual, Augmented, and Mixed Reality for Human-Robot Interaction (VAM-HRI). HRI (Companion) 2020: 663-664 - [i3]Serena Booth, Ankit Shah, Yilun Zhou, Julie Shah:
Sampling Prediction-Matching Examples in Neural Networks: A Probabilistic Programming Approach. CoRR abs/2001.03076 (2020) - [i2]Serena Booth, Yilun Zhou, Ankit J. Shah, Julie A. Shah:
Bayes-Probe: Distribution-Guided Sampling for Prediction Level Sets. CoRR abs/2002.10248 (2020) - [i1]Yilun Zhou, Serena Booth, Nadia Figueroa, Julie Shah:
RoCUS: Robot Controller Understanding via Sampling. CoRR abs/2012.13615 (2020)
2010 – 2019
- 2019
- [c2]Serena Booth, Christian Muise, Julie Shah:
Evaluating the Interpretability of the Knowledge Compilation Map: Communicating Logical Statements Effectively. IJCAI 2019: 5801-5807 - 2017
- [c1]Serena Booth, James Tompkin, Hanspeter Pfister, Jim Waldo, Krzysztof Gajos, Radhika Nagpal:
Piggybacking Robots: Human-Robot Overtrust in University Dormitory Security. HRI 2017: 426-434
Coauthor Index
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