williamSYSU/CatGAN

Codes for Category-aware Generative Adversarial Networks (AAAI 2020)

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Emerging

This project helps researchers and developers working with text generation to create synthetic text that accurately reflects specific categories. It takes in existing categorized text data and generates new, diverse text samples that belong to those predefined categories. This is ideal for those in academic research or applied natural language processing who need to expand datasets or test models with category-specific text.

No commits in the last 6 months.

Use this if you need to generate realistic, category-specific text for research or development purposes, such as expanding training datasets or creating synthetic data.

Not ideal if you are looking for a ready-to-use application for content creation or customer-facing text generation, as this is a research-oriented codebase.

text-generation natural-language-processing synthetic-data AI-research categorized-text
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 15 / 25

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19

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License

MIT

Last pushed

Sep 04, 2020

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