For natural language inference, the same encoder is used to encode both the premise and hypothesis and a concatenation of their representations along with the absolute difference and hadamard product (as described in <cite>Conneau et al. (2017)</cite> ) are given to a single layer MLP with a dropout (Srivastava et al., 2014 ) rate of 0.3.