Decoding NCM's latents reveals coarse-to-fine text generation trajectory
Azaliamirh · x · 2026-10-15
By decoding NCM's intermediate latent representations into text at each generation step, Hermann Kumbong shows its generation is coarse-to-fine: the model progressively adds finer details to the text as it traverses its hierarchy, rather than emitting complete text at once. A neat window into how hierarchical generative models build up output.
More from Research
- Explainer: why MiniMax's CISPO variant of GRPO preserves the tokens that signal CoT self-correction — andrew_n_carr · 2026-10-15
- Why RL lacks scaling laws: pretraining optimizes loss, open-ended maximization the lightcone — akbirthko · 2026-10-15
- zPocket: open cofolding-feature pocket predictor hits 0.745 AUPRC, beats P2Rank — LotfiSanae · 2026-10-15
- 500-question Gemini study: product named = 78% web search, need described = 7% — MattWags_33 · 2026-10-15
- NCM: new text generation paradigm up to 31x faster than diffusion LMs with better quality — simonguozirui · 2026-10-15
- UC Berkeley wins $1.7M Google.org grant for AI-driven medical discovery — 2plus2make5 · 2026-10-15