To allow the learning system to explore more powerful transformation, we follow the design of the 'affine coupling layer' (Dinh et al., 2016): where s : are both neural networks with linear output units, and • is the Hadamard product.
current ways of incorporating the distributional hypothesis only utilise it as a weak and noisy supervision, which might limit the quality of the learnt sentence representations.