We also introduce a new inference algorithm for iterative parallel decoding, parallel easy-first, where each word is predicted by attending to the words that the model is more confident about. This decoding algorithm allows for predicting all tokens with different context in each iteration and terminates when the output prediction converges, contrasting with the constant number of iterations<cite> (Ghazvininejad et al., 2019)</cite> .