We present a probabilistic generative model for learning semantic parsers from ambiguous supervision. Our approach learns from natural language sentences paired with world states ...
Obtaining performance models, like Markov chains and queueing networks, for systems of significant complexity and magnitude is a difficult task that is usually tackled using human...
We present a novel approach for the automatic generation of model-to-model transformations given a description of the operational semantics of the source language in the form of gr...
Previous work has shown that high quality phrasal paraphrases can be extracted from bilingual parallel corpora. However, it is not clear whether bitexts are an appropriate resourc...
Juri Ganitkevitch, Chris Callison-Burch, Courtney ...
Designer's productivity has become the key-factor of the development of electronic systems. An increasing application of design data reuse is widely recognized as a promising...