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Closed Book Training to Improve Summarization Encoder Memory

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Figure 1: Baseline model repeats itself twice (italic),and fails to find all salient information (highlighted inred in the original text) from the source text that is cov-ered by our 2-decoder model
Figure 2: Our 2-decoder summarization model with a pointer decoder and a closed-book decoder, both sharing asingle encoder (this is during training; next, at inference time, we only employ the memory-enhanced encoder andthe pointer decoder).
Table 2:ROUGE F1 and METEOR scores (with-coverage) on the CNN/Daily Mail test set.Cover-age mechanism (See et al., 2017) is used in all mod-els except the RL model (Paulus et al., 2018).Themodel marked with ⋆ is trained and evaluated on theanonymized version of the data.
Table 5: Cosine-similarity between memory states aftertwo forward passes.
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