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This paper describes multimodal machine translation systems developed jointlyby Oregon State University and Baidu Research for WMT 2018 Shared Task onmultimodal translation. In this paper, we introduce a simple approach toincorporate image information by feeding image features to the decoder side. Wealso explore different sequence level training methods including scheduledsampling and reinforcement learning which lead to substantial improvements. Oursystems ensemble several models using different architectures and trainingmethods and achieve the best performance for three subtasks: En-De and En-Cs intask 1 and (En+De+Fr)-Cs task 1B.

Ensemble Sequence Level Training for Multimodal MT: OSU-Baidu WMT18 Multimodal Machine Translation System Report