This document summarizes a research paper that proposes incorporating discrete translation lexicons into neural machine translation. The paper introduces methods to encode low-frequency words using lexicon probabilities as either a bias or through linear interpolation. Evaluation on English-Japanese translation tasks showed the methods improved BLEU scores by 2.0-2.3 and NIST scores by 0.13-0.44, while also achieving faster convergence time during training.