Most notably, for the natural language inference task, augmenting the hypothesis (u) and premise (v) representations with |u−v| and u · v considerably improves performance in a siamese architecture <cite>Mou et al. (2016)</cite> . In this paper we focus on polynomial features like u · v for the natural language inference task, where it is trying to capture similarity between u and v. It is also a monomial of degree 2.