Review for NeurIPS paper: Multi-agent Trajectory Prediction with Fuzzy Query Attention

Weaknesses: The experiments have been extensive, however I have following three crucial questions to better understand the performance boost arising from the overall architecture: 1. Improvement arising from interaction module or motion module? Taking Social LSTM [1] to be an interaction-based baseline, the proposed architecture has two different components: the interaction and motion modules. Is the boost coming from the interaction module which is FQA in comparison to Social Pooling [1]? Or is it the new motion module? An ablation study showing the performance while keeping the motion module the same as the baseline will help answer this question. The authors use the term Fuzzy to describe continuous-valued decisions over their discrete-valued boolean counterparts.