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	<pub:Misc rdf:about="http://ebiquity.umbc.edu/paper/html/id/940/Deep-Learning-for-Category-Free-Grounded-Language-Acquisition">
		<rdfs:label><![CDATA[Deep Learning for Category-Free Grounded Language Acquisition]]></rdfs:label>
		<pub:title><![CDATA[Deep Learning for Category-Free Grounded Language Acquisition]]></pub:title>
		<pub:publishedOn rdf:datatype="&xsd;dateTime">2019-06-01T00:00:00-05:00</pub:publishedOn>
		<pub:abstract><![CDATA[We propose a learning system in which language is grounded in visual percepts without pre-defined category constraints. We present a unified generative method to acquire a shared semantic/visual embedding that enables a more general language grounding acquisition system. We evaluate the efficacy of this learning by predicting the semantics of ground truth objects and comparing the performance with each of a predefined category classifier and a simple logistic regression classifier. Our preliminary results suggest that this generative approach exhibits promising results in language grounding without pre-specifying visual categories such as color and shape.]]></pub:abstract>
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		<pub:tag><![CDATA[natural language processing]]></pub:tag>
		<pub:tag><![CDATA[robotics]]></pub:tag>
		<pub:booktitle><![CDATA[NAACL Workshop on Spatial Language Understanding and Grounded Communication for Robotics]]></pub:booktitle>
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					<person:Person rdf:about="http://ebiquity.umbc.edu/person/html/Cynthia/Matuszek"><person:name><![CDATA[Cynthia Matuszek]]></person:name><rdfs:label><![CDATA[Cynthia Matuszek]]></rdfs:label></person:Person>
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