L 1 regularization method (Tsuruoka et al., 2009)  model with the +id feature setting on both the development set and training data set, respectively, and their hyperameters are tuned on the dev-test set.
experiments on IWSLT Chineseto-english translation tasks show that, with the help of grouping these features, our method can overcome the above pitfalls and thus achieves significant improvements.