#image-generation

5 articles

01 ·★ MEMBER·PAPER·8 min read Paper Explained: SenseNova-U1.5 — One Model That Both Sees and Draws, With No Encoder and No VAE SenseNova-U1.5 is an 8B unified model that learns straight from pixels and words, with no vision encoder for understanding and no VAE for generation. We walk through its seam-free spatial decoder and its 'train specialists separately, then distill them into one' post-training, following the paper itself. 02 ·Agents·★ MEMBER·PAPER·11 min read Editable Visual Design, explained — demoting image generation to a sketch and shipping the artifact as HTML The image model stops being the deliverable and becomes an imagination engine plus an asset factory, while a coding agent rebuilds the piece in HTML/CSS. A walk through the paper behind posters whose layers come apart and whose text is real text. 03 ·★ 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. 04 ·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. 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.