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...
Abstract. We show that several previously proposed passage-based document ranking principles, along with some new ones, can be derived from the same probabilistic model. We use lan...
In this paper, we propose a new Bayesian model for fully unsupervised word segmentation and an efficient blocked Gibbs sampler combined with dynamic programming for inference. Our...
In statistical language modeling, one technique to reduce the problematic effects of data sparsity is to partition the vocabulary into equivalence classes. In this paper we invest...