A Neural Multi-sequence Alignment TeCHnique (NeuMATCH)
Table 6: Performance of ablated models in the one-to-many setting (3-action model).
['[EMPTY]', '[BOLD] HM-1  [BOLD] clips', '[BOLD] HM-1  [BOLD] sent. IoU', '[BOLD] HM-2  [BOLD] clips', '[BOLD] HM-2  [BOLD] sent. IoU']
The four ablated models perform substantially worse than the complete model. This confirms our intuition that both the history and the future play important roles in sequence alignment. We conclude that all four LSTM stacks contribute to NeuMATCH’s superior performance.