Papers with Generating natural language

2 papers
Multi-Task Neural Models for Translating Between Styles Within and Across Languages (C18-1)

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Challenge: Generating natural language requires conveying content in an appropriate style.
Approach: They propose to solve two related tasks on generating text of varying formality jointly using multi-task learning.
Outcome: The proposed models achieve state-of-the-art performance for formality transfer and formality-sensitive machine translation without training on style-annotated translation examples.
Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach (2020.findings-emnlp)

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Challenge: Generating natural language under complex constraints is a principled formulation towards controllable text generation.
Approach: They propose a method to specify combinatorial constraints for sentence generation . they use a tree search algorithm embedded into the proposal process of the Markov Chain Monte Carlo .
Outcome: The proposed method achieves consistent and significant improvement on multiple language generation tasks.

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