Over the weekend, I was using codex to update my homepage and a paper I wrote a year ago on the topic of diffusion LLMs (should be updated on Monday).
https://t.co/qvqldZ9H1w
While I did not want to make it too explicit back then, I have argued that discrete diffusion LLMs were not the right thing to do and if diffusion ever works on LLMs continuous dLLMs are the way to go.
A year later, we are seeing a lot cool papers in this space, and I hope the community can push for something practical and scalable.
😢just a note to every researcher on pixel diffusion that PixNerd is the FIRST large patch diffusion transformer on pixels without vaes.. please do not ignore and give the proper credit to it
The main idea behind D-AR is to **bridge** AR and diffusion via the proposed visual tokenizer. Therefore, we can perform diffusion on image space by **the simple next token prediction**!
❓What do you think about image diffusion process "simulated" by an autoregressive LLM?
+ 🎨 Diffusion quality
+ ⚡️ LLM-style inference with KV caching
+ 🔢 Discrete tokens in & discrete tokens out
That's D-AR! Diffusion via Autoregressive Models
Code: https://t.co/WEN8J5DLET
❓What do you think about image diffusion process "simulated" by an autoregressive LLM?
+ 🎨 Diffusion quality
+ ⚡️ LLM-style inference with KV caching
+ 🔢 Discrete tokens in & discrete tokens out
That's D-AR! Diffusion via Autoregressive Models
Code: https://t.co/WEN8J5DLET
❓What do you think about image diffusion process "simulated" by an autoregressive LLM?
+ 🎨 Diffusion quality
+ ⚡️ LLM-style inference with KV caching
+ 🔢 Discrete tokens in & discrete tokens out
That's D-AR! Diffusion via Autoregressive Models
Code: https://t.co/WEN8J5DLET
❓What do you think about image diffusion process "simulated" by an autoregressive LLM?
+ 🎨 Diffusion quality
+ ⚡️ LLM-style inference with KV caching
+ 🔢 Discrete tokens in & discrete tokens out
That's D-AR! Diffusion via Autoregressive Models
Code: https://t.co/WEN8J5DLET
Near 500 paper claimed in Space ICLR 2024🎉
https://t.co/vTDeyBkXfT
Here are some tips if you want to engage more with the community 🤗
💡 Join the discussion threads below each paper.
💡 Start a conversation with authors by clicking "@" next to the author's profile photo on their @huggingface account.
💡 Link your models, datasets, and demos to your papers.
#ICLR2024 @_akhaliq
🚀 Our latest survey paper is now released, presenting a comprehensive analysis of hallucination phenomena in multimodal large language models (MLLMs), also known as Large Vision-Language Models (LVLMs).
arXiv: https://t.co/8L4FC1QHvT
GitHub: https://t.co/YkLJl7XtgY
😁SparseFormer finally got accepted at ICLR 2024 @iclr_conf !! Big thanks to all co-authors!!
⚡️A sparse visual architecture that can understand an image with down to only 9 tokens in the latent space.
🤖️Code for images is released and please give a try! @_akhaliq
Thank @_akhaliq previous featured our work. Videoswap is now accepted by CVPR 2024. The code is now available at https://t.co/hwwOhSHVsA. Welcome to try!