Papers with attention-driven hypothesis

1 papers
Rethinking Model Selection and Decoding for Keyphrase Generation with Pre-trained Sequence-to-Sequence Models (2023.emnlp-main)

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Challenge: Keyphrase generation is a longstanding task in NLP with widespread applications.
Approach: They propose a likelihood-based decode-select algorithm for seq2seq PLMs that improves greedy search by an average of 4.7% semantic F1 across five datasets.
Outcome: The proposed algorithm improves greedy search by an average of 4.7% semantic F1 across five datasets.

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