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Investigating the Impact of Experience on a User's Ability to Perform Hierarchical Abstraction., , , , , , , and . Robotics: Science and Systems, (2023)Guiding Multi-Step Rearrangement Tasks with Natural Language Instructions., , , , , , and . CoRL, volume 164 of Proceedings of Machine Learning Research, page 1486-1501. PMLR, (2021)Learning to Ground Natural Language Instructions to Plans.. Brown University, USA, (2020)Learning to Parse Natural Language to Grounded Reward Functions with Weak Supervision., , , and . ICRA, page 1-7. IEEE, (2018)Planning Hierarchies and their Connections to Language.. AAAI Spring Symposia, AAAI Press, (2018)Simultaneously Learning Transferable Symbols and Language Groundings from Perceptual Data for Instruction Following., , , and . Robotics: Science and Systems, (2020)Flight, Camera, Action! Using Natural Language and Mixed Reality to Control a Drone., , , , and . ICRA, page 6949-6956. IEEE, (2019)Feedback error learning for rhythmic motor primitives., , and . ICRA, page 1317-1322. IEEE, (2013)Sequence-to-Sequence Language Grounding of Non-Markovian Task Specifications., , , and . Robotics: Science and Systems, (2018)Negative Result for Learning from Demonstration: Challenges for End-Users Teaching Robots with Task And Motion Planning Abstractions., , , and . Robotics: Science and Systems, (2022)