However, we leave more advanced encoder and QA matching design for future work, and anticipate that more complex CNN based models can achieve similar or better results than our current design, as in many other QA-related work (Hu et al., 2014; . (2) Compared with the best result from<cite> (Yang et al., 2015)</cite> in Table 1 , training the CNN based model end-to-end using our objective improves from 32.17% to 35.03%.