Papers with top-down decoding

2 papers
Efficient Constituency Parsing by Pointing (2020.acl-main)

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Challenge: Constituency parsing is a core task in natural language processing (NLP) Existing methods for constituency paring are greedy transition-based or globally optimized.
Approach: They propose a constituency parsing model that casts the problem into a series of pointing tasks.
Outcome: The proposed model achieves 92.78 F1 without pre-trained models, which is faster than existing models.
A Conditional Splitting Framework for Efficient Constituency Parsing (2021.acl-long)

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Challenge: Developing efficient and effective parsing solutions has always been a key focus in NLP.
Approach: They propose a generic seq2seq parsing framework that casts constituency parsers into a series of conditional splitting decisions.
Outcome: The proposed framework outperforms state-of-the-art (SoTA) methods in discourse parsing . it is based on a syntactic and discourse parsed model and is linear in number of nodes .

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