Papers with attention-based encoder-decoder framework

1 papers
Generalized Supervised Attention for Text Generation (2021.findings-acl)

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Challenge: Existing supervised attention methods that use human knowledge to learn better alignments are costly or infeasible.
Approach: They propose a generalized supervised attention method based on quasi alignments that are easier to obtain than ideal alignments.
Outcome: The proposed framework improves generation performance and is robust against errors in attention supervision.

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