Review for NeurIPS paper: Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games

The work is an interesting approach of extending KG-A2C with sub-graphs to achieve impressive state of the art performance on several games. Ablation studies show that this architecture is needed to achieve the performance and the attention analysis is interesting. The work could benefit from a more thorough analysis of what the model is doing (beyond just attention values which are questionable). The paper could also benefit from improved clarity in its writing.