Browsing by Author "Shieber, Stuart"

Now showing items 41-60 of 94

    • The influence of task contexts on the decision-making of humans and computers. 

      Gal, Ya'akov Kobi; Grosz, Barbara; Pfeffer, Avrom; Shieber, Stuart; Allain, Alex (Springer, 2007)
      Many environments in which people and computer agents interact involve deploying resources to accomplish tasks and satisfy goals. This paper investigates the way that the context in which decisions are made affects the ...

    • Infrastructure for Research towards Ubiquitous Information Systems 

      Grosz, Barbara J.; Kung, H. T.; Seltzer, Margo I.; Shieber, Stuart Merrill; Smith, Michael D. (1994)
      The availability of fast, inexpensive computers and the growth of network technology have resulted in the proliferation of computing power and an enormous increase in information available in electronic form. However, most ...

    • An interactive constraint-based system for drawing graphs 

      Ryall, Kathy; Marks, Joe; Shieber, Stuart (Association for Computing Machinery, 1997)
      The glide system is an interactive constraint-based editor for drawing small- and medium-sized graphs (50 nodes or fewer) that organizes the interaction in a more collaborative manner than in previous systems. Its ...

    • An interactive system for drawing graphs 

      Ryall, Kathy; Marks, Joe; Shieber, Stuart (Springer, 1996)
      Abstract: In spite of great advances in the automatic drawing of medium and large graphs, the tools available for drawing small graphs exquisitely (that is, with the aesthetics commonly found in professional publications ...

    • An Introduction to Unification-Based Approaches to Grammar 

      Shieber, Stuart M. (Microtome Publishing, 2003)

    • Inverting the Turing Test [review of The Most Human Human by Brian Christian] 

      Shieber, Stuart M. (Sigma Xi, 2011)
      In his book The Most Human Human, Brian Christian extrapolates from his experiences at the 2009 Loebner Prize competition, a competition among chatbots (computer programs that engage in conversation with people) to see ...

    • Is this article consistent with Hinchliffe's rule? 

      Shieber, Stuart Merrill (2015)
      I demonstrate that Hinchliffe’s rule – if the title of a scholarly article is a yes-no question, the answer is “no” – is paradoxical, by providing an article whose title is a question whose answer is “no” if and only if ...

    • Labeling Point Features on Maps and Diagrams 

      Christensen, Jon; Marks, Joe; Shieber, Stuart Merrill (1992)
      A major factor affecting the clarity of graphical displays that include text labels is the degree to which labels obscure display features (including other labels) as a result of spatial overlap. Point-feature label placement ...

    • A Language for Specifying Informational Graphics from First Principles 

      Shieber, Stuart M.; Lucas, Wendy (Springer-Verlag, 2007)
      Informational visualization tools, such as commercial charting packages, provide a standard set of visualizations for tabular data, including bar charts, scatter plots, pie charts, and the like. For some combinations of ...

    • Learning Neural Templates for Text Generation 

      Wiseman, Sam; Shieber, Stuart; Rush, Alexander Sasha (Association for Computational Linguistics, 2018-10)
      While neural, encoder-decoder models have had significant empirical success in text generation, there remain several unaddressed problems with this style of generation. Encoder-decoder models are largely (a) uninterpretable, ...

    • Lessons from a restricted Turing test 

      Shieber, Stuart (Association for Computing Machinery, 1994)
      We report on the recent Loebner prize competition inspired by Turing's test of intelligent behavior. The presentation covers the structure of the competition and the outcome of its first instantiation in an actual event, ...

    • Lexical Chaining and Word-Sense-Disambiguation 

      Nelken, Rani; Shieber, Stuart M. (2007)
      Lexical chains algorithms attempt to find sequences of words in a document that are closely related semantically. Such chains have been argued to provide a good indication of the topics covered by the document without ...

    • Lexical Chaining and Word-Sense-Disambiguation 

      Nelken, Rani; Shieber, Stuart Merrill (2007)
      Lexical chains algorithms attempt to find sequences of words in a document that are closely related semantically. Such chains have been argued to provide a good indication of the topics covered by the document without ...

    • LSTM Networks Can Perform Dynamic Counting 

      Suzgun, Mirac; Gehrmann, Sebastian; Belinkov, Yonatan; Shieber, Stuart (2019-06-09)
      In this paper, we systematically assess the ability of standard recurrent networks to perform dynamic counting and to encode hierarchical representations. All the neural models in our experiments are designed to be small-sized ...

    • Machine learning theory and practice as a source of insight into universal grammar. 

      Lappin, Shalom; Shieber, Stuart (Cambridge University Press, 2007)
      In this paper, we explore the possibility that machine learning approaches to natural-language processing being developed in engineering-oriented computational linguistics may be able to provide specific scientific insights ...

    • Neo-Riemannian Cycle Detection with Weighted Finite-State Transducers 

      Bragg, Jonathan; Chew, Elaine; Shieber, Stuart M. (University of Miami, 2011)
      This paper proposes a finite-state model for detecting harmonic cycles as described by neo-Riemannian theorists. Given a string of triads representing a harmonic analysis of a piece, the task is to identify and label all ...

    • Nonparametric Bayesian Inference and Efficient Parsing for Tree-adjoining Grammars 

      Yamangil, Elif; Shieber, Stuart M. (Association for Computational Linguistics, 2013)
      In the line of research extending statistical parsing to more expressive grammar formalisms, we demonstrate for the first time the use of tree-adjoining grammars (TAG). We present a Bayesian nonparametric model for estimating ...

    • On Adversarial Removal of Hypothesis-only Bias in Natural Language Inference 

      Belinkov, Yonatan; Poliak, Adam; Shieber, Stuart; Van Durme, Benjamin; Rush, Alexander Sasha (2019-06)
      Popular Natural Language Inference (NLI) datasets have been shown to be tainted by hypothesis-only biases. Adversarial learning may help models ignore sensitive biases and spurious correlations in data. We evaluate whether ...

    • On Evaluating the Generalization of LSTM Models in Formal Languages 

      Suzgun, Mirac; Belinkov, Yonatan; Shieber, Stuart (Society for Computation in Linguistics, 2019-01)
      Recurrent Neural Networks (RNNs) are theoretically Turing-complete and established themselves as a dominant model for language processing. Yet, there still remains an uncertainty regarding their language learning capabilities. ...

    • Optimal k-arization of synchronous tree-adjoining grammar 

      Nesson, Rebecca; Satta, Giorgio; Shieber, Stuart (Association for Computational Linguistics, 2008)
      Synchronous Tree-Adjoining Grammar (STAG) is a promising formalism for syntax-aware machine translation and simultaneous computation of natural-language syntax and semantics. Current research in both of these areas is ...