Incorporating Stylistic Lexical Preferences in Generative Language Models Article Swipe
YOU?
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· 2020
· Open Access
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· DOI: https://doi.org/10.18653/v1/2020.findings-emnlp.96
While recent advances in language modeling have resulted in powerful generation models, their generation style remains implicitly dependent on the training data and can not emulate a specific target style. Leveraging the generative capabilities of a transformer-based language models, we present an approach to induce certain target-author attributes by incorporating continuous multi-dimensional lexical preferences of an author into generative language models. We introduce rewarding strategies in a reinforcement learning framework that encourages the use of words across multiple categorical dimensions, to varying extents. Our experiments demonstrate that the proposed approach can generate text that distinctively aligns with a given target author's lexical style. We conduct quantitative and qualitative comparisons with competitive and relevant baselines to illustrate the benefits of the proposed approach.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.18653/v1/2020.findings-emnlp.96
- https://www.aclweb.org/anthology/2020.findings-emnlp.96.pdf
- OA Status
- gold
- References
- 20
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3093823402
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3093823402Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.18653/v1/2020.findings-emnlp.96Digital Object Identifier
- Title
-
Incorporating Stylistic Lexical Preferences in Generative Language ModelsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-01-01Full publication date if available
- Authors
-
Hrituraj Singh, Gaurav Verma, B. SrinivasanList of authors in order
- Landing page
-
https://doi.org/10.18653/v1/2020.findings-emnlp.96Publisher landing page
- PDF URL
-
https://www.aclweb.org/anthology/2020.findings-emnlp.96.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.aclweb.org/anthology/2020.findings-emnlp.96.pdfDirect OA link when available
- Concepts
-
Generative grammar, Computer science, Categorical variable, Transformer, Artificial intelligence, Style (visual arts), Language model, Generative model, Natural language processing, Reinforcement learning, Language understanding, Machine learning, Engineering, Archaeology, History, Voltage, Electrical engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
-
20Number of works referenced by this work
- Related works (count)
-
20Other works algorithmically related by OpenAlex
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| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.75 |
| sustainable_development_goals[0].display_name | Quality Education |
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| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |