In our project, we explore the potential extensions to the Neural Collaborative Filtering (NCF) Framework to improve model understanding and robustness. Using additional Convolutional layers, Pairwise Loss Function and Auxiliary Information Embedding, we experiment with the MovieLens-1M dataset to attain better model performance on Hit Rate and NDCG metrics while attempting to improve model understanding through auxiliary embeddings.