Multi-Cast Attention Networks for Retrieval-based Question Answering and Response Prediction
Table 5. Ablation analysis (validation set) on TrecQA dataset.
['Setting', 'MAP', 'MRR']
This section aims to demonstrate the relative effectiveness of different components of our proposed MCAN model. We report the scores of seven different configurations. In (1), we replace all highway layers with regular feed-forward neural networks. In (2), we remove the LSTM encoder before the prediction layer. In (3), we remove the entire multi-cast attention mechanism. This is equivalent to removing the twelve attention features. In (4-7), we remove different attention casts, aiming to showcase that removing either one results in some performance drop.