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Multi-Task Minimum Error Rate Training for SMT We present experiments on multi-task learning for discriminative training in statistical machine translation (SMT), extending standard minimum-error-rate training (MERT) by techniques that take advantage of the similarity of related tasks. We apply our techniques to German-to-English translation of patents from 8 tasks according to the International Patent Classification (IPC) system. Our experiments show statistically significant gains overdoi:10.2478/v10108-011-0015-0 fatcat:eepkepl6lnhkld2bizwytesrn4