Current re-ranking algorithms for machine translation rely on log-linear models, which have the potential problem of underfitting the training data. We present BoostedMERT, a nove...
This paper proposes dynamic semantics for agent communication languages (ACLs) as a method for tackling some of the fundamental problems associated with agent communication in ope...
Adaptor grammars (Johnson et al., 2007b) are a non-parametric Bayesian extension of Probabilistic Context-Free Grammars (PCFGs) which in effect learn the probabilities of entire s...
Given several systems' automatic translations of the same sentence, we show how to combine them into a confusion network, whose various paths represent composite translations...
Damianos Karakos, Jason Eisner, Sanjeev Khudanpur,...
Abstract. Agent Communication Languages (ACLs) play a fundamental role in open multiagent systems where message exchange is the main if not the only way for agents to coordinate th...