Exploring the limits of transfer learning with a unified text-to-text transformer.

Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., and Chen, M. (2022). Hierarchical text-conditional image

generation with clip latents.

15

Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., Chen, M., and Sutskever, I. (2021).

Zero-shot text-to-image generation.

mapping in text2image models.

with latent diffusion models.

Segmentation. arXiv:1505.04597.

Rassin, R., Ravfogel, S., and Goldberg, Y. (2022). Dalle-2 is seeing double: Flaws in word-to-concept

Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B. (2022). High-resolution image synthesis

Ronneberger, O., Fischer, P., and Brox, T. (2015). U-Net: Convolutional Networks for Biomedical Image
Improving Image Generation with Better Captions