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Table 6: Results of different training strategies on MSR-VTT with the best semantic features.
['Training Method', 'B-4', 'C', 'M', 'R', 'Overall']
Teacher Forcing utilizes human annotations to guide the generation of words during training and samples from the word distribution of the output of the model to direct the generation during inference. argmax gradually transfers from teacher forcing way to sample words with the largest possibility from the model itself during training. Multinomial is close to argmax but samples words at random from the distribution of the model at each step. Our method explores RNN state space in larger scope and thus, is likely to find a lower local minimum during training.