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1
Neural Variational Learning for Grounded Language Acquisition ...
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2
Measuring Perceptual and Linguistic Complexity in Multilingual Grounded Language Data ...
Pillai, Nisha; Matuszek, Cynthia; Ferraro, Francis. - : University of Florida Press, 2021
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3
Neural Variational Learning for Grounded Language Acquisition ...
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4
Neural Variational Learning for Grounded Language Acquisition ...
RO-MAN 2021 2021; Ferraro, Francis; Matuszek, Cynthia. - : Underline Science Inc., 2021
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5
Sampling Approach Matters: Active Learning for Robotic Language Acquisition ...
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6
Sampling Approach Matters: Active Learning for Robotic Language Acquisition ...
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7
Learning Natural Language from Probabilistic Perceptual Representations with Limited Resources ...
Mannukkunnel Balan Pillai, Nisha. - : Maryland Shared Open Access Repository, 2020
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8
Building Language-Agnostic Grounded Language Learning Systems ...
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9
Building Language-Agnostic Grounded Language Learning Systems ...
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10
Deep Learning for Category-Free Grounded Language Acquisition ...
Pillai, Nisha; Ferraro, Francis; Matuszek, Cynthia. - : Maryland Shared Open Access Repository, 2019
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11
Building Language-Agnostic Grounded Language Learning Systems ...
Kery, Caroline; Pillai, Nisha; Matuszek, Cynthia. - : Maryland Shared Open Access Repository, 2019
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12
Optimal Semantic Distance for Negative Example Selection in Grounded Language Acquisition ...
Pillai, Nisha; Ferraro, Francis; Matuszek, Cynthia. - : Workshop on Models and Representations for Natural Human-Robot Communication 2018, 2018
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13
Unsupervised Selection of Negative Examples for Grounded Language Learning ...
Pillai, Nisha; Matuszek, Cynthia. - : AAAI, 2018
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14
Identifying Negative Exemplars in Grounded Language Data Sets ...
Pillai, Nisha; Matuszek, Cynthia. - : Robotics: Science and Systems (R:SS) Workshop on Spatial-Semantic Representations in Robotics, 2017
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15
Improving Grounded Language Acquisition Efficiency Using Interactive Labeling ...
Pillai, Nisha; Budhraja, Karan K.; Matuszek, Cynthia. - : Robotics: Science and Systems (R:SS), 2016
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