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1
Zero-shot learning to execute tasks with robots
Alverio, Julian(Julian A.). - : Massachusetts Institute of Technology, 2020
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2
Understanding language through visual imagination
Mao, Cheahuychou.. - : Massachusetts Institute of Technology, 2019
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3
Second language learning from a multilingual perspective
Berzak, Yevgeni. - : Massachusetts Institute of Technology, 2018
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4
Minimal characterization of linguistic phenomena for robust ternary expression construction
Tong, Jason Kar Chun. - : Massachusetts Institute of Technology, 2018
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5
Grounded semantic parsing using captioned videos
Ross, Candace Cheronda. - : Massachusetts Institute of Technology, 2018
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6
Using a symbolic language parser to Improve Markov language models
Townsend, Duncan Clarke McIntire. - : Massachusetts Institute of Technology, 2015
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7
CLAIRE makes machine translation BLEU no more
Mohammad, Ali (Ali H.). - : Massachusetts Institute of Technology, 2012
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8
Identifying power relationships in dialogues
Shen, Yuan Kui. - : Massachusetts Institute of Technology, 2011
Abstract: Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. ; This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. ; Cataloged from student submitted PDF version of thesis. ; Includes bibliographical references (p. 175-179). ; Understanding power relationships is an important step towards building computers that can understand human social relationships. Power relationships can arise due to dierences in the roles of the speakers, as between bosses and employees. Power can also affect the manner of communication between social equals, as between friends or acquaintances. There are numerous potential uses for an automatic system that can understand power relationships. These include: the analysis of the organizational structure of formal and ad-hoc groups, the profiling of in influential individuals within a group, or identifying aggressive or power-inappropriate language in email or other Internet media. In this thesis, we explore the problem of engineering eective power identication systems. We show methods for constructing an eective ground truth corpus for analyzing power. We focus on three areas of modeling that help in improving the prediction of power relationships. 1) Utterance Level Language Cues - patterns of language use can help distinguish the speech of leaders or followers. We show a set of eective syntactic/semantic features that best capture these linguistic manifestations of power. 2) Dialog Level Interactions - the manner of interaction between speakers can inform us about the underlying power dynamics. We use Hidden Markov Models to organize and model the information from these interaction-based cues. 3) Social conventions - speaker behavior is in influenced by their background knowledge, in particular, conventional rules of communication. We use a generative hierarchical Bayesian framework to model dialogs as mental processes; then we extend these models to include components that encode basic social conventions such as politeness. We apply our integrated system, PRISM, on the Nixon Watergate Transcripts, to demonstrate that our system can perform robustly on real world data. ; by Yuan Kui Shen. ; Ph.D.
Keyword: Electrical Engineering and Computer Science
URL: http://hdl.handle.net/1721.1/68178
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9
Natural Language and Spatial Reasoning
In: http://people.csail.mit.edu/stefie10/publications/stefie10-thesis-proposal.pdf (2010)
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10
Sepia: a Framework for Natural Language Semantics
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11
Answering English Questions using ForeignLanguage, Semi-Structured Sources
In: http://groups.csail.mit.edu/infolab/publications/Katz-ForeignLanguage.pdf (2007)
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12
Nuggeteer: Automatic Nugget-Based Evaluation Using Descriptions and Judgements
Marton, Gregory. - 2006
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13
Lexical chains and sliding locality windows in contentbased text similarity detection
In: http://publications.csail.mit.edu/tmp/MIT-CSAIL-TR-2005-034.pdf (2005)
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14
Using Syntactic Information to Identify Plagiarism
In: http://acl.ldc.upenn.edu/W/W05/W05-0207.pdf (2005)
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15
A Comparative Study of Language Models for Book and Author Recognition
In: http://people.csail.mit.edu/ozlem/ijcnlp-05-UzunerO.pdf (2005)
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16
Syntactic and semantic decomposition strategies for question answering from multiple resources
In: http://www.hlt.utdallas.edu/workshop2005/papers/Katz-Multiple-Resources.pdf (2005)
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17
Syntactic and semantic decomposition strategies for question answering from multiple resources
In: http://www.aaai.org/Papers/Workshops/2005/WS-05-05/WS05-05-006.pdf (2005)
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18
Lexical chains and sliding locality windows in contentbased text similarity detection
In: http://acl.ldc.upenn.edu/I/I05/I05-2026.pdf (2005)
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19
Capturing Expression Using Linguistic Information
In: https://www.aaai.org/Papers/AAAI/2005/AAAI05-178.pdf (2005)
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20
Identifying expression fingerprints using linguistic information
Uzuner, Ozlem, 1975-. - : Massachusetts Institute of Technology, 2005
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