Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to i...
In this paper, we introduce a method that automatically builds text classifiers in a new language by training on already labeled data in another language. Our method transfers the...
This paper introduces a class of statistical mechanisms, called hidden understanding models, for natural language processing. Much of the framework for hidden understanding models...
Scott Miller, Richard M. Schwartz, Robert J. Bobro...
Probabilistic processes appear naturally in various contexts, with applications to Business Processes, XML data management and more. Many models for specifying and querying such p...
In the context of Model Driven Development, models play a central role. Since models can nowadays be executed, they are used not only for description but also for production [32][3...