Synth^2 is a new approach that leverages large language models and text-to-image generators to create synthetic image-caption data for boosting visual-language model performance.
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Synth^2 is a new approach that leverages large language models and text-to-image generators to create synthetic image-caption data for boosting visual-language model performance.
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Key Points:
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Key Points:
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* Overcomes data limitations by generating high-quality synthetic image-caption pairs, reducing reliance on costly human annotations.
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* Overcomes data limitations by generating high-quality synthetic image-caption pairs, reducing reliance on costly human annotations.
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* Achieves competitive results on image captioning tasks using 40x less paired data than state-of-the-art methods.
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* Achieves competitive results on image captioning tasks using 40x less paired data than state-of-the-art methods.
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Paper: 
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Paper: 
Synth$^2$: Boosting Visual-Language Models with Synthetic Captions and
  Image Embeddings (2403.07750)
https://huggingface.co/papers/2403.07750
2403.07750
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https://huggingface.co/papers/2403.07750
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Congrats to the authors for their work!
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Congrats to the authors for their work!
Synth^2 is a new approach that leverages large language models and text-to-image generators to create synthetic image-caption data for boosting visual-language model performance.

Key Points:
* Overcomes data limitations by generating high-quality synthetic image-caption pairs, reducing reliance on costly human annotations.
* Achieves competitive results on image captioning tasks using 40x less paired data than state-of-the-art methods.

Paper: https://huggingface.co/papers/2403.07750

Congrats to the authors for their work!
❤️
samusenps osanseviero Zmu
👍
CocoSun Wauplin