Post
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: Synth$^2$: Boosting Visual-Language Models with Synthetic Captions and Image Embeddings (2403.07750)
Congrats to the authors for their work!
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: Synth$^2$: Boosting Visual-Language Models with Synthetic Captions and Image Embeddings (2403.07750)
Congrats to the authors for their work!