Before revision:  Using simulated experiments, we demonstrate that MT model stealing is possible even when imitation models have different input data or architectures than their victims . Applying these ideas, we train imitation models that reach within 0.6 BLEU of three production MT systems on both high-resource and low-resource language pairs.
After revision:  Using simulated experiments, we demonstrate that MT model stealing is possible even when imitation models have different input data or architectures than their target models . Applying these ideas, we train imitation models that reach within 0.6 BLEU of three production MT systems on both high-resource and low-resource language pairs.