Next-Concept建模：快速并行粗到精文本生成

Computer Science > Computation and Language

arXiv:2610.14162 (cs)

[Submitted on 9 Oct 2026]

Title: Next-Concept Modeling: Fast, Parallel Coarse-to-Fine Text Generation

View a PDF of the paper titled Next-Concept Modeling: Fast, Parallel Coarse-to-Fine Text Generation, by Hermann Kumbong and 8 other authors

View PDF HTML (experimental)

> Abstract: Diffusion language models (DLMs) offer parallel sampling for faster generation than autoregressive models, an increasingly important advantage as inference becomes a dominant computational workload. However, DLMs degrade quickly with fewer sampling steps, process the full sequence at every step, and require many passes over the dataset to reach good quality. We introduce Next-Concept Modeling (NCM), a two-stage, coarse-to-fine framework: a multiscale residual VQ-VAE encodes text into a hierarchy of discrete codes, and a transformer generates one level at a time, predicting all codes within a level in parallel. At matched parameter scales, NCM achieves better generative perplexity than the strongest DLM baseline on LM1B while running $21\times$ faster. On OpenWebText, NCM is competitive with the strongest DLM while running $10\times$ faster; on XSum, it matches the strongest DLM's ROUGE-L while being $31\times$ faster. On the reasoning task of Sudoku, NCM outperforms autoregressive and diffusion baselines across all difficulty levels, using fewer function evaluations. On the reasoning task of Sudoku, NCM outperforms autoregressive and diffusion baselines across all difficulty levels, using fewer function evaluations.

Subjects:

Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Machine Learning (cs.LG)

Cite as: arXiv:2610.14162 [cs.CL]

(or arXiv:2610.14162v1 [cs.CL] for this version)

arXiv-issued DOI via DataCite

Submission history

From: Hermann Kumbong [view email] [v1] Fri, 9 Oct 2026 17:49:45 UTC (352 KB)

Full-text links:

Access Paper:

View a PDF of the paper titled Next-Concept Modeling: Fast, Parallel Coarse-to-Fine Text Generation, by Hermann Kumbong and 8 other authors

View PDF

· HTML (experimental)