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Devleena Das
Devleena Das
Research Scientist II, Georgia Institute of Technology
在 gatech.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Explainable ai for robot failures: Generating explanations that improve user assistance in fault recovery
D Das, S Banerjee, S Chernova
Proceedings of the 2021 ACM/IEEE International Conference on Human-Robot …, 2021
1162021
Leveraging rationales to improve human task performance
D Das, S Chernova
Proceedings of the 25th International Conference on Intelligent User …, 2020
462020
Explainable activity recognition for smart home systems
D Das, Y Nishimura, RP Vivek, N Takeda, ST Fish, T Ploetz, S Chernova
ACM Transactions on Interactive Intelligent Systems 13 (2), 1-39, 2023
312023
State2explanation: Concept-based explanations to benefit agent learning and user understanding
D Das, S Chernova, B Kim
Advances in Neural Information Processing Systems 36, 67156-67182, 2023
212023
Semantic-Based Explainable AI: Leveraging Semantic Scene Graphs and Pairwise Ranking to Explain Robot Failures
D Das, S Chernova
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021
212021
Reprogramming pretrained language models for antibody sequence infilling
I Melnyk, V Chenthamarakshan, PY Chen, P Das, A Dhurandhar, I Padhi, ...
International Conference on Machine Learning, 24398-24419, 2023
172023
Vision-based detection of simultaneous kicking for identifying movement characteristics of infants at-risk for neuro-disorders
D Das, K Fry, AM Howard
2018 17th IEEE International Conference on Machine Learning and Applications …, 2018
162018
Subgoal-based explanations for unreliable intelligent decision support systems
D Das, B Kim, S Chernova
Proceedings of the 28th International Conference on Intelligent User …, 2023
132023
Explainable knowledge graph embedding: Inference reconciliation for knowledge inferences supporting robot actions
A Daruna, D Das, S Chernova
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022
92022
DEFT: Data Efficient Fine-Tuning for Large Language Models via Unsupervised Core-Set Selection
D Das, V Khetan
arXiv preprint arXiv:2310.16776, 2023
22023
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