| Explaining explanations: An overview of interpretability of machine learning LH Gilpin, D Bau, BZ Yuan, A Bajwa, M Specter, L Kagal 2018 IEEE 5th International Conference on data science and advanced …, 2018 | 3102 | 2018 |
| Outracing champion Gran Turismo drivers with deep reinforcement learning PR Wurman, S Barrett, K Kawamoto, J MacGlashan, K Subramanian, ... Nature 602 (7896), 223-228, 2022 | 477 | 2022 |
| Graph analysis for detecting fraud, waste, and abuse in healthcare data J Liu, E Bier, A Wilson, JA Guerra-Gomez, T Honda, K Sricharan, L Gilpin, ... Ai Magazine 37 (2), 33-46, 2016 | 107 | 2016 |
| Can large language models explain themselves? a study of llm-generated self-explanations S Huang, S Mamidanna, S Jangam, Y Zhou, LH Gilpin arXiv preprint arXiv:2310.11207, 2023 | 49 | 2023 |
| Explaining Explanations to Society LH Gilpin, C Testart, N Fruchte, J Adebayo arXiv preprint arXiv:1901.06560, 2018 | 45 | 2018 |
| Perception of speaker personality traits using speech signals LH Gilpin, DM Olson, T Alrashed Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing …, 2018 | 33 | 2018 |
| Monitoring scene understanders with conceptual primitive decomposition and commonsense knowledge LH Gilpin, JC Macbeth, E Florentine Advances in Cognitive Systems 6, 45-63, 2018 | 20 | 2018 |
| Reasonableness monitors LH Gilpin Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | 17 | 2018 |
| " Explanation" is Not a Technical Term: The Problem of Ambiguity in XAI LH Gilpin, AR Paley, MA Alam, S Spurlock, KJ Hammond arXiv preprint arXiv:2207.00007, 2022 | 14 | 2022 |
| Explaining multimodal errors in autonomous vehicles LH Gilpin, V Penubarthi, L Kagal 2021 IEEE 8th International Conference on Data Science and Advanced …, 2021 | 13 | 2021 |
| A stress testing framework for autonomous system verification and validation (v&v) G Falco, LH Gilpin 2021 IEEE International Conference on Autonomous Systems (ICAS), 1-5, 2021 | 10 | 2021 |
| Anomaly detection through explanations LH Gilpin Massachusetts Institute of Technology, 2020 | 10 | 2020 |
| Establishing meta-decision-making for AI: an ontology of relevance, representation and reasoning C Badea, L Gilpin arXiv preprint arXiv:2210.00608, 2022 | 9 | 2022 |
| Autonomous Driving with Spiking Neural Networks RJ Zhu, Z Wang, L Gilpin, JK Eshraghian arXiv preprint arXiv:2405.19687, 2024 | 8 | 2024 |
| Co-simulation solutions using AA4MM-FMI applied to smart space heating models L Gilpin, L Ciarletta, Y Presse, V Chevrier, V Galtier Seventh International Conference on Simulation Tools and Techniques, 2014 | 8 | 2014 |
| Separating facts and evaluation: motivation, account, and learnings from a novel approach to evaluating the human impacts of machine learning R Jenkins, K Hammond, S Spurlock, L Gilpin AI & SOCIETY 38 (4), 1415-1428, 2023 | 6 | 2023 |
| The anticipatory paradigm A Amos‐Binks, D Dannenhauer, LH Gilpin AI Magazine 44 (2), 133-143, 2023 | 6 | 2023 |
| Towards a fuller understanding of neurons with Clustered Compositional Explanations B La Rosa, L Gilpin, R Capobianco Advances in Neural Information Processing Systems 36, 2024 | 5 | 2024 |
| Anticipatory thinking: A testing and representation challenge for self-driving cars LH Gilpin 2021 55th annual conference on information sciences and systems (CISS), 1-2, 2021 | 5 | 2021 |
| A knowledge driven approach to adaptive assistance using preference reasoning and explanation JR Wilson, L Gilpin, I Rabkina arXiv preprint arXiv:2012.02904, 2020 | 5 | 2020 |
Lalana KagalMassachusetts Institute of Technologycsail.mit.edu의 이메일 확인됨