EveryDream2trainer/doc/CITATIONS.md

Everydream 2 trainer is built using various open source technologies and packages.

This is not a thorough nor deep list, but is an opinionated list of research that is most proximal to this repo and interesting.

### Stable Diffusion's Predecessors and Components

AutoencoderKL [paper](https://arxiv.org/abs/1312.6114v11)

DDPM [paper](https://arxiv.org/abs/2006.11239) - [github](https://github.com/hojonathanho/diffusion)

CLIP [paper](https://arxiv.org/pdf/2103.00020.pdf) - [github](https://github.com/OpenAI/CLIP)

OpenClip [info](https://laion.ai/blog/large-openclip/) - [github](https://github.com/mlfoundations/open_clip)

LAION 5B [paper](https://arxiv.org/abs/2210.08402) - [datasets](https://huggingface.co/laion)

### Latent Diffusion
Latent Diffusion [paper](https://arxiv.org/abs/2112.10752) - [github](https://github.com/CompVis/latent-diffusion) -- Stable Diffusion [github](https://github.com/CompVis/stable-diffusion)

SDXL [paper](https://arxiv.org/abs/2307.01952) - [github](https://github.com/Stability-AI/generative-models)


### Captioning models

Open Flamingo [paper](https://arxiv.org/abs/2308.01390) - [github](https://github.com/mlfoundations/open_flamingo)

BLIP/BLIP2 [blip paper](https://arxiv.org/abs/2201.12086) - [blip2 github (LAVIS)](https://github.com/salesforce/LAVIS) - [blip1 github](https://github.com/salesforce/BLIP)

Kosmos-2 [paper](https://arxiv.org/abs/2306.14824) - [Github](https://github.com/microsoft/unilm/tree/master/kosmos-2) - [Huggingface](https://huggingface.co/microsoft/kosmos-2-patch14-224)

Cog-VLM [paper](https://arxiv.org/abs/2311.03079) - [Github](https://github.com/THUDM/CogVLM) - [Huggingface](https://huggingface.co/THUDM/cogvlm-chat-hf)


### Optimizers

Adam [paper](https://arxiv.org/abs/1412.6980)

8-bit block-wise quantization [paper](https://arxiv.org/abs/2110.02861) - [github](https://github.com/TimDettmers/bitsandbytes)

D-Adaptation [paper](https://arxiv.org/abs/2301.07733) - [github](https://github.com/facebookresearch/dadaptation)

DoWG [paper](https://arxiv.org/abs/2305.16284)