Incremental parsing techniques such as shift-reduce have gained popularity thanks to their efficiency, but there remains a major problem: the search is greedy and only explores a ...
Hierarchical HMM (HHMM) parsers make promising cognitive models: while they use a bounded model of working memory and pursue incremental hypotheses in parallel, they still achieve...
Stephen Wu, Asaf Bachrach, Carlos Cardenas, Willia...
Automatic error detection is desired in the post-processing to improve machine translation quality. The previous work is largely based on confidence estimation using system-based ...
The pipeline of most Phrase-Based Statistical Machine Translation (PB-SMT) systems starts from automatically word aligned parallel corpus. But word appears to be too fine-grained ...
There is a growing research interest in opinion retrieval as on-line users' opinions are becoming more and more popular in business, social networks, etc. Practically speakin...
Linear Context-Free Rewriting Systems (LCFRSs) are a grammar formalism capable of modeling discontinuous phrases. Many parsing applications use LCFRSs where the fan-out (a measure...
We describe our experiments with training algorithms for tree-to-tree synchronous tree-substitution grammar (STSG) for monolingual translation tasks such as sentence compression a...
In this paper, we formulate extractive summarization as a risk minimization problem and propose a unified probabilistic framework that naturally combines supervised and unsupervis...