Halfway through its 12 sweeps, a Next-Concept Model story is word salad with the characters already in place. I built a browser player that replays real generations level by level so you can watch that sharpening happen.
What NCM is. Next-Concept Modeling (NCM), from HazyResearch at Stanford, generates text coarse to fine (paper: arXiv 2610.14162). A multiscale residual VQ tokenizer represents a story as 12 nested sets of discrete codes, growing from 1 concept code to 128. A transformer predicts that whole hierarchy with one forward pass per level, not one token at a time.
What I built. A static page in vanilla JavaScript: no server, no GPU in the browser. The trajectories are real generations from the released TinyStories checkpoint (the generator is 356MB, the tokenizer 222MB), captured on CPU with a small script included in the repo. For each of the 12 sweeps the player shows the tokenizer's partial reconstruction of the codes generated so far. The same story, sharpening.
What the replays show. The split is sharp. By level 6 of 12 the partial decode is word salad, but the character names are already sitting in place. The text only becomes readable in the last three sweeps. Nine of twelve sweeps are not readable on their own: the model decides what the story is about early, and legibility arrives late.
Why a replay beats a demo video. A video plays once. A trajectory can be stopped at any level, scrubbed back, and compared sweep to sweep. You can see exactly when Lily and Ben appear, and what the model still gets wrong one level before the end.
Try the player here: NCM Trajectory. Code and the capture script are on GitHub. The paper is Next-Concept Modeling, arXiv 2610.14162 by HazyResearch; the trajectories come from the checkpoint they released, and the page explains the finding by itself.
