generally solve these two problems separately or iteratively. In this work, we propose a unified frame-work for simultaneous human parsing and pose estima-tion based on semantic parts. By utilizing Parselets and Mixture of Joint-Group Templates as the representations for these semantic parts, we seamlessly

to data from a recent experiment in human associative learning (J. K. Kruschke 6 N. J. Blair, 2000, Psychonomic Bulletin 6 Review, 7, 636 645), which shows that blocking of learning involves learned inattention. The approach also provides a novel and unifying theory of latent inhibition (the preexposure

The World Wide Web promises to transform human society by making virtually all types of information instantly available everywhere. Two prerequisites for this promise to be realized are a universal markup language and a universal query language. The power and flexibility of XML make

introduction to a theory treated in much more detail in [STin]. Formalizations, proofs and detailed discussions can be found there. Because of limited space we can present only some underlying ideas of a theory which unifies all context-free parsing techniques known to the author. We hope to convince

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. Whether a syntactic description is used as a parser or as a pretty-printer is determined by the implementation of the interface. Syntactic descriptions enable programmers syntax once and for all, and use these descriptions for parsing or pretty-printing as needed. We also discuss the generalization of our

this paper we discuss our research and development towards creating an architecture, and a story design using this architecture, that integrates a broad and shallow approach to natural language processing, a novel character authoring language and a novel drama manager, in order to build

Abstract: Humans can effortlessly understand a lot of what is going on in other peoples ’ minds. Understanding the neural basis of this capacity has proven quite difficult. Since the discovery of mirror neurons, a number of successful experiments have approached the question of how we understand

There is strong evidence that human sentence processing is incremental, i.e., that structures are built word by word. Recent experiments show that the processor also predicts upcoming linguistic material on the basis of previous input. We present a computational model of human parsing that is based

Is there a single mechanism that underlies all perceptual and cognitive processing? This paper aims to solve a small part of Newell's challenge (A. Newell 1990, Unified Theories of Cognition, Harvard University Press) and proposes a model that unifies three different modalities: language