Tracking the World State with Recurrent Entity Networks
Table 6: Results on bAbI Tasks with 1k samples.
['Task', 'MemN2N', 'EntNet']
We provide some additional experiments on the bAbI tasks, in order to better understand the influence of architecture, weight tying, and amount of training data. Here, the EntNet still performs better than a MemN2N which uses the same encoding scheme, indicating that the architecture has an important effect. Tying the key vectors to entities did not help, and hurt performance for some tasks. In this setting, the EntNet performs worse than the MemN2N.