The model follows an encoder-decoder architecture where a convolutional neural network encodes an image of a mathematical formula and a recurrent decoder with attention generates the corresponding LaTeX sequence. It includes beam search for improved decoding and was inspired by the Show, Attend and Tell paper and Harvard’s im2markup dataset.