Papers with constrained decoding approach

2 papers
Constrained Decoding for Neural NLG from Compositional Representations in Task-Oriented Dialogue (P19-1)

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Challenge: Generating fluent natural language responses from structured semantic representations is a critical step in task-oriented conversational systems.
Approach: They propose using tree-structured semantic representations for better discourse-level structuring and sentence-level planning and introduce a challenging dataset using this representation for the weather domain.
Outcome: The proposed model improves discourse-level structuring and sentence-level planning on a weather domain and can be decoded to improve semantic correctness.
The Mechanical Bard: An Interpretable Machine Learning Approach to Shakespearean Sonnet Generation (2023.acl-short)

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Challenge: Rather than train a model to obey these constraints implicitly, we opt to enforce them explicitly using a simple but novel approach to generation.
Approach: They propose to automate the generation of sonnets within preset poetic constraints using a constrained decoding approach that uses a relatively modest neural backbone.
Outcome: The proposed method produces sonnets that adhere to the genre’s defined constraints and contain lyrical language and literary devices.

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