Bibliography (16):

1. ​ GPT-3 Creative Fiction § BPEs

2. DALL·E 2: Hierarchical Text-Conditional Image Generation with CLIP Latents § 7. Limitations and Risks

3. Models In a Spelling Bee: Language Models Implicitly Learn the Character Composition of Tokens

4. ByT5 model for massively multilingual grapheme-to-phoneme conversion

5. T5: Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

6. PaLM: Scaling Language Modeling with Pathways

7. Imagen: Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding

8. https://arxiv.org/pdf/2212.10562.pdf#page=3&org=google

9. Stable Diffusion Public Release

10. DALL·E 1: Creating Images from Text: We’ve trained a neural network called DALL·E that creates images from text captions for a wide range of concepts expressible in natural language

11. Hierarchical Text-Conditional Image Generation with CLIP Latents

12. https://parti.research.google/

13. eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers

14. mT5: A massively multilingual pre-trained text-to-text transformer

15. ByT5: Towards a token-free future with pre-trained byte-to-byte models

16. Wikipedia Bibliography:

    1. https://en.wikipedia.org/wiki/BPE  :

       https://en.wikipedia.org/wiki/BPE