This paper proposes a general learning framework for a class of problems that require learning over latent intermediate representations. Many natural language processing (NLP) dec...
Ming-Wei Chang, Dan Goldwasser, Dan Roth, Vivek Sr...
We investigate in this paper the adequate unit of analysis for Arabic Mention Detection. We experiment different segmentation schemes with various feature-sets. Results show that ...
We present results from a range of experiments on article and preposition error correction for non-native speakers of English. We first compare a language model and errorspecific ...
In this paper, we describe an approach based on off-the-shelf parsers and semantic resources for the Recognizing Textual Entailment (RTE) challenge that can be generally applied t...
In this paper we propose a novel general framework for unsupervised model adaptation. Our method is based on entropy which has been used previously as a regularizer in semi-superv...
Ariya Rastrow, Frederick Jelinek, Abhinav Sethy, B...