#image-generation
5 articles
01
·★ MEMBER·PAPER·9 min read
Paper Walkthrough: LLaDA-Image — Building the Visual Prior from Images Alone, Then Distilling to 2–4 Steps
A training recipe that builds the visual prior from images alone before any caption enters the picture. We walk through LLaDA-Image — a 6B DiT trained from scratch and distilled down to 2–4 sampling steps — following the design decisions the paper actually makes.
02
·★ MEMBER·PAPER·10 min read
Paper Explained — GenFirst: Let Generation Shape the Latent Space First, Reconstruction Second
Image generation normally means training a VAE first and bolting a generative model onto its frozen latent space. This paper trains both at once without latent collapse — the key is the entropy term inside the KL objective, plus a simple rule: let generation go first and ramp reconstruction up later.
03
·Inference & Serving·★ MEMBER·PAPER·13 min read
Paper explained: Self-OPD — an image generator that distills itself, with no teacher
No teacher model at all: at every denoising step the student spawns K copies of itself, scores them, and pulls toward the good branches while pushing away from the bad ones. A ground-up walkthrough of Self-OPD, an alignment method for flow matching image generators.
04
·★ MEMBER·PAPER·9 min read
Paper Walkthrough: On-Policy Self-Distillation in Diffusion Models — Turning Reward into a Target You Can Aim At
When you train an image generator with rewards, a score on the finished picture never tells the model how to change its intermediate denoising predictions. DiffusionOPSD builds explicit targets from reward gradients and fits them using an EMA copy of the model itself. A ground-up explanation, strictly within what the abstract states.
05
·Agents·★ MEMBER·PAPER·8 min read
Paper Walkthrough: ToolArtist — Search, Draw, or Redraw? The Image Agent That Decides for Itself
Drawing "a harvester collecting dragon's blood resin on Socotra in 1955" correctly takes less artistic skill than research. ToolArtist makes searching, reasoning, and drawing all actions of a single policy — a fully agentic image generator. We walk through the conversion trick behind its SFT data, the dual-reward RL scheme (RAD-GRPO), and the 0.79 WISE result, straight from the paper.