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README.md
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Without any labeled downstream pairs for training, ZeroNLG is an unified framework that deals with multiple natural language generation (NLG) tasks in a zero-shot manner, including image-to-text, video-to-text, and text-to-text generation tasks across English, Chinese, German, and French.
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Pre-trained data: a machine-translated version of [CC3M](https://huggingface.co/datasets/conceptual_captions), including
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- 1.1M English sentences
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- 1.1M English-Chinese pairs
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- 1.1M English-German pairs
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- 1.1M English-French pairs
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Paper: [ZeroNLG: Aligning and Autoencoding Domains for Zero-Shot Multimodal and Multilingual Natural Language Generation](https://arxiv.org/abs/2303.06458)
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Authors: *Bang Yang\*, Fenglin Liu\*, Yuexian Zou, Xian Wu, Yaowei Wang, David A. Clifton*
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Without any labeled downstream pairs for training, ZeroNLG is an unified framework that deals with multiple natural language generation (NLG) tasks in a zero-shot manner, including image-to-text, video-to-text, and text-to-text generation tasks across English, Chinese, German, and French.
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[Pre-trained data](https://drive.google.com/file/d/1yCLpDLDO5TnoqfyHKwgi51Fw66QliOvM/view?usp=share_link): a machine-translated version of [CC3M](https://huggingface.co/datasets/conceptual_captions), including
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- 1.1M English sentences
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- 1.1M English-Chinese pairs
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- 1.1M English-German pairs
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- 1.1M English-French pairs
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Paper: [ZeroNLG: Aligning and Autoencoding Domains for Zero-Shot Multimodal and Multilingual Natural Language Generation](https://arxiv.org/abs/2303.06458)
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Authors: *Bang Yang\*, Fenglin Liu\*, Yuexian Zou, Xian Wu, Yaowei Wang, David A. Clifton*
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