We present a probabilistic generative model for learning semantic parsers from ambiguous supervision. Our approach learns from natural language sentences paired with world states ...
Via an oracle experiment, we show that the upper bound on accuracy of a CCG parser is significantly lowered when its search space is pruned using a supertagger, though the supert...
In this paper, we demonstrate that accurate machine translation is possible without the concept of “words,” treating MT as a problem of transformation between character string...
Graham Neubig, Taro Watanabe, Shinsuke Mori, Tatsu...
Object-oriented, concurrent, and event-based programming models provide a natural framework in which to express the behavior of distributed and embedded software systems. However,...
Johan Nordlander, Mark P. Jones, Magnus Carlsson, ...
Towards a unifying model of concurrency, we have designed and implemented LMNtal (pronounced "elemental"), a model and language based on hierarchical graph rewriting tha...