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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=grounded+language">
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  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=grounded+language]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for grounded language]]></description>
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      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1150/Multimodal-Language-Learning-for-Object-Retrieval-in-Low-Data-Regimes-in-the-Face-of-Missing-Modalities"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/968/Sampling-Approach-Matters-Active-Learning-for-Robotic-Language-Acquisition"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/950/Practical-Cross-modal-Manifold-Alignment-for-Grounded-Language"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/951/Presentation-and-Analysis-of-a-Multimodal-Dataset-for-Grounded-Language-Learning"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/916/Building-Language-Agnostic-Grounded-Language-Learning-Systems"/>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1150/Multimodal-Language-Learning-for-Object-Retrieval-in-Low-Data-Regimes-in-the-Face-of-Missing-Modalities">
  <title><![CDATA[Multimodal Language Learning for Object Retrieval in Low Data Regimes in the Face of Missing Modalities]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1150/Multimodal-Language-Learning-for-Object-Retrieval-in-Low-Data-Regimes-in-the-Face-of-Missing-Modalities</link>
  <description><![CDATA[Our study is motivated by robotics, where when dealing with robots or other physical systems, we often need to balance competing concerns of relying on complex, multimodal data coming from a variety of sensors with a general lack of large representative datasets.  Despite the complexity of modern robotic platforms and the need for multimodal interaction, there has been little research on integrating more than two modalities in a low data regime with the real-world constraint that sensors fail...]]></description>
  <dc:date>2023-10-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1062/Bridging-the-Gap-Using-Deep-Acoustic-Representations-to-Learn-Grounded-Language-from-Percepts-and-Raw-Speech">
  <title><![CDATA[Bridging the Gap: Using Deep Acoustic Representations to Learn Grounded Language from Percepts and Raw Speech]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1062/Bridging-the-Gap-Using-Deep-Acoustic-Representations-to-Learn-Grounded-Language-from-Percepts-and-Raw-Speech</link>
  <description><![CDATA[Learning to understand grounded language, which connects natural language to percepts, is a critical research area. Prior work in grounded language acquisition has focused primarily on textual inputs. In this work, we demonstrate the feasibility of performing grounded language acquisition on paired visual percepts and raw speech inputs. This will allow human-robot interactions in which language about novel tasks and environments is learned from end-users, reducing dependence on textual inputs...]]></description>
  <dc:date>2022-06-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1003/Neural-Variational-Learning-for-Grounded-Language-Acquisition">
  <title><![CDATA[Neural Variational Learning for Grounded Language Acquisition]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1003/Neural-Variational-Learning-for-Grounded-Language-Acquisition</link>
  <description><![CDATA[We propose a learning system in which language
is grounded in visual percepts without specific pre-defined
categories of terms. We present a unified generative method
to acquire a shared semantic/visual embedding that enables
the learning of language about a wide range of real-world
objects. We evaluate the efficacy of this learning by predicting
the semantics of objects and comparing the performance with
neural and non-neural inputs. We show that this generative
approach exhibits pro...]]></description>
  <dc:date>2021-08-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/973/Measuring-Perceptual-and-Linguistic-Complexity-in-Multilingual-Grounded-Language-Data">
  <title><![CDATA[Measuring Perceptual and Linguistic Complexity in Multilingual Grounded Language Data]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/973/Measuring-Perceptual-and-Linguistic-Complexity-in-Multilingual-Grounded-Language-Data</link>
  <description><![CDATA[The success of grounded language acquisition using perceptual data (e.g., in robotics) is affected by the complexity of both the perceptual concepts being learned and the language describing those concepts. We present methods for analyzing this complexity, using both visual features and entropy-based evaluation of sentences. Our work illuminates core, quantifiable statistical differences in how language is used to describe different traits of objects, and the visual representation of those ob...]]></description>
  <dc:date>2021-05-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/984/A-Simulator-for-Human-Robot-Interaction-in-Virtual-Reality">
  <title><![CDATA[A Simulator for Human-Robot Interaction in Virtual Reality]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/984/A-Simulator-for-Human-Robot-Interaction-in-Virtual-Reality</link>
  <description><![CDATA[We present a suite of tools to model a robot, its sensors, and the surrounding environment in VR, with the goal of collecting training data for real-world robots. The virtual robot observes a rigged avatar created in our photogrammetry facility and embodying a VR user.  We are particularly interested in verbal human/robot interactions, which can be combined with the robot’s sensor data for grounded language learning. Because virtual scenes, tasks, and robots are easily reconfigured compared...]]></description>
  <dc:date>2021-03-27</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/985/Towards-Making-Virtual-Human-Robot-Interaction-a-Reality">
  <title><![CDATA[Towards Making Virtual Human-Robot Interaction a Reality]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/985/Towards-Making-Virtual-Human-Robot-Interaction-a-Reality</link>
  <description><![CDATA[For robots deployed in human-centric spaces, natural language promises an intuitive, natural interface. However, obtaining appropriate training data for grounded language in a variety of settings is a significant barrier. In this work, we describe using human-robot interactions in virtual reality to train a robot, combining fully simulated sensing and actuation with human interaction. We present the architecture of our simulator and our grounded language learning approach, then describe our i...]]></description>
  <dc:date>2021-03-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/968/Sampling-Approach-Matters-Active-Learning-for-Robotic-Language-Acquisition">
  <title><![CDATA[Sampling Approach Matters: Active Learning for Robotic Language Acquisition]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/968/Sampling-Approach-Matters-Active-Learning-for-Robotic-Language-Acquisition</link>
  <description><![CDATA[Ordering the selection of training data using active learning can lead to improvements in learning efficiently from smaller corpora. We present an exploration of active learning approaches applied to three grounded language problems of varying complexity in order to analyze what methods are suitable for improving data efficiency in learning. We present a method for analyzing the complexity of data in this joint problem space, and report on how characteristics of the underlying task, along wit...]]></description>
  <dc:date>2020-12-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/950/Practical-Cross-modal-Manifold-Alignment-for-Grounded-Language">
  <title><![CDATA[Practical Cross-modal Manifold Alignment for Grounded Language]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/950/Practical-Cross-modal-Manifold-Alignment-for-Grounded-Language</link>
  <description><![CDATA[We propose a cross-modality manifold alignment procedure that leverages triplet loss to jointly learn consistent, multi-modal embeddings of language-based concepts of real-world items. Our approach learns these embeddings by sampling triples of anchor, positive, and negative data points from RGB-depth images and their natural language descriptions. We show that our approach can benefit from, but does not require, post-processing steps such as Procrustes analysis, in contrast to some of our ba...]]></description>
  <dc:date>2020-09-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/951/Presentation-and-Analysis-of-a-Multimodal-Dataset-for-Grounded-Language-Learning">
  <title><![CDATA[Presentation and Analysis of a Multimodal Dataset for Grounded Language Learning]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/951/Presentation-and-Analysis-of-a-Multimodal-Dataset-for-Grounded-Language-Learning</link>
  <description><![CDATA[Grounded language acquisition -- learning how language-based interactions refer to the world around them -- is a major area of research in robotics, NLP, and HCI. In practice, the data used for learning consists almost entirely of textual descriptions, which tend to be cleaner, clearer, and more grammatical than actual human interactions. In this work, we present the Grounded Language Dataset (GoLD), a multimodal dataset of common household objects described by people using either spoken or w...]]></description>
  <dc:date>2020-07-31</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/916/Building-Language-Agnostic-Grounded-Language-Learning-Systems">
  <title><![CDATA[Building Language-Agnostic Grounded Language Learning Systems]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/916/Building-Language-Agnostic-Grounded-Language-Learning-Systems</link>
  <description><![CDATA[Learning the meaning of grounded language—
language that references a robot’s physical environment and
perceptual data—is an important and increasingly widely studied problem in robotics and human-robot interaction. However,
with a few exceptions, research in robotics has focused on
learning groundings for a single natural language pertaining
to rich perceptual data. We present experiments on taking
an existing natural language grounding system designed for
English and applying i...]]></description>
  <dc:date>2019-10-14</dc:date>
 </item>
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