In this paper, with a belief that a language model that embraces a larger context provides better prediction ability, we present two extensions to standard n-gram language models ...
This paper makes a case for the definition of a family of languages for expressing patterns over both the structure and semantics of source code. Our proposal is unique in that i...
In this paper, we propose a novel string-todependency algorithm for statistical machine translation. With this new framework, we employ a target dependency language model during d...
This paper reports our efforts on developing a language modeling approach to passage question answering. In particular, we address the following two problems: (i) generalized lang...
Syntactic machine translation systems currently use word alignments to infer syntactic correspondences between the source and target languages. Instead, we propose an unsupervised...