🚀【Large Language Diffusion Models】#DiffusionModels #LLM #LLaDA We built LLaDA-8B—the FIRST non-autoregressive model rivaling LLaMA3! CRUSHES Llama2-7B on ~20 tasks while unlocking ICL/instruction-following/multi-turn chat

Since the behaviors of consistency models are quite different in pixel and latent spaces, I wonder if using these new AEs can further improve the training of consistency models

Still think consistency models are bad at scale? In fact, sCM can be stably scaled to modern text-to-image diffusion models and greatly improve the generation speed and 1-step generation quality!

we finally know

Lots of fun w/ Gabriel Goh Lu Liu A Jabri Kenji Hata Jianfeng Wang Dian Ang Yap Prafulla Dhariwal

kinda true

if you want to see someone truly passionate about image generation, look no further than Gabriel Goh he lives and breathes making image generation wonderful.

fixed this with 4o

Congrats on everyone who worked in the GPT-4o image generation team! It’s really impressive and I’m so proud of us! It was also quite enjoyable working with such a group of talented people!

I closely worked with and learned a lot from Gabriel Goh and A Jabri , and it can be summarized in the old saying: be the change you want to see

I’ve changed so little. From my 1978 Bachelor’s thesis: “The adult human mind is very complex, but the question remains open whether the learning processes that constructed it in interaction with the environment are similarly complex. Much evidence and many peoples’ intuitions

So true

A very promising direction for real-time video generation! arxiv.org/abs/2506.01380 nextframed.github.io 1. You can always use DPM-Solver++ to accelerate your flow matching model. 2. sCM can even scale to video diffusion model and boost the sample quality a lot!

So true

I didn't want to post on Grok safety since I work at a competitor, but it's not about competition. I appreciate the scientists and engineers at xAI but the way safety was handled is completely irresponsible. Thread below.

Congrats! This is an incredible milestone and I was truly shocked by it. “Thinking for hours” means 10x or even 100x of current test-time compute, and I can’t wait to see the model think for days, months, years, centuries to solve the science challenges!

Exact same feeling