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Building agents capable of understanding language instructions is critical to effective and robust human-AI collaboration.
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Accurately and efficiently interpreting human-robot instructions of varying granularities
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A tale of two draggns: A hybrid approach for interpreting action-oriented and goal-oriented instructions
S. Karamcheti, E. C. Williams, D. Arumugam, M. Rhee, N. Gopalan, L. L. S. Wong, and S. Tellex · 2017
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D. K. Misra, J. Langford, and Y. Artzi · 2017
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D. Pathak, P. Agrawal, A. A. Efros, and T. Darrell · 2017
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Proximal policy optimization algorithms
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Reinforced cross-modal matching and self-supervised imitation learning for vision-language navigation
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N. Waytowich, S. L. Barton, V. Lawhern, and G. Warnell · 2019
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Experience grounds language
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F. Hill, S. Mokra, N. Wong, and T. Harley · 2020
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Alfred: A benchmark for interpreting grounded instructions for everyday tasks
M. Shridhar, J. Thomason, D. Gordon, Y. Bisk, W. Han, R. Mottaghi, L. Zettlemoyer, and D. Fox · 2020
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