Debate Flares Over Autoregressive vs Diffusion Training Efficiency
A viral analysis argued autoregressive training gains efficiency by splitting length-T contexts into T input-output pairs, making non-causal diffusion models data-hungry; mgostIH added that DeepSeek V4.1 could have used a non-causal encoder, citing a CMU paper showing diffusion wins in data-constrained settings.
2026-09-11 ~ 2026-09-11 · 4 related posts
- Dev argues DeepSeek V4.1 could have used a non-causal encoder for stronger reasoning — mgostIH · 2026-09-11
- Why Non-Causal Training Is Data-Inefficient — And What DeepSeek V4.1 Could Have Done — ThePremiseOfIt · 2026-09-11
- Autoregressive vs Diffusion Training: The Data-Efficiency Math Behind Non-Causal Architectures — mgostIH · 2026-09-11
- Diffusion beats autoregressive models when data is scarce, CMU paper finds — mgostIH · 2026-09-11