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Controlling Linguistic Style Aspects in Neural Language Generation

arXiv 1707.02633 ↗First posted 9 Jul 2017cs.CLcited by 147

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Abstract (arXiv)

Most work on neural natural language generation (NNLG) focus on controlling the content of the generated text. We experiment with controlling several stylistic aspects of the generated text, in addition to its content. The method is based on conditioned RNN language model, where the desired content as well as the stylistic parameters serve as conditioning contexts. We demonstrate the approach on the movie reviews domain and show that it is successful in generating coherent sentences corresponding to the required linguistic style and content.

Key facts. Cited by 147 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jul 2017.

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Citing papers per year: 2021: 30; 2022: 38; 2023: 31; 2024: 23; 2025: 16; 2026: 9.

147 papers.

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38 more
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