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We present a unified framework which supports grounding natural-language semantics in robotic driving.
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Teaching a robot spatial expressions
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Harris, T. K., Banerjee, S., and Rudnicky, A. I. (2005) · 2005
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Semantic processing using the hidden vector state model
He, Y. and Young, S. (2005) · 2005
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Driving semantic parsing from the world’s response
Clarke, J., Goldwasser, D., Chang, M.-W., and Roth, D. (2010) · 2010
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Kollar, T., Tellex, S., Roy, D., and Roy, N. (2010) · 2010
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A voice-commandable robotic forklift working alongside humans in minimally-prepared outdoor environments
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Chen, D. L. and Mooney, R. J. (2011) · 2011
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Reading between the lines: Learning to map high-level instructions to commands
Branavan, S. R. K., Zettlemoyer, L. S., and Barzilay, R. (2010) · 2010
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Understanding natural language commands for robotic navigation and mobile manipulation
Tellex, S., Kollar, T., Dickerson, S., Walter, M. R., Banerjee, A. G., Teller, S. J., and Roy, N. (2011) · 2011
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Seeing what you’re told: Sentence-guided activity recognition in video
Siddharth, N., Barbu, A., and Siskind, J. M. (2014) · 2014
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Learning perceptually grounded word meanings from unaligned parallel data
Tellex, S., Thaker, P., Joseph, J., and Roy, N. (2014) · 2014
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