Diffusion LM compute gap falls from 17.8x to 3.0x, step by step
volokuleshov · x · 2026-10-16
Each change quantified: 17.8x → 12.8x (exact likelihood) → 9.6x → 7.8x, down to 3.0x at block size 4. The fits hold at a held-out budget 3x beyond the fitted range, and zero-shot accuracy tracks the likelihood ranking.
Related event: Cornell-Amazon Study Debunks the 16x Compute Gap Claim for Diffusion LMs(6 posts)→
More from Research
- Open-source 12-chapter guide builds a modern LLM from scratch with every line commented — tom_doerr · 2026-10-16
- John Nash's 1998 Hierarchical Introspective Logics paper recirculates in AI circles — fkasummer · 2026-10-16
- Ex-OpenAI interp lead: most neurons in trillion-param models are now legible — CatAstro_Piyush · 2026-10-16
- AI safety researcher: most technical safety topics echo classic statistics from 20-70 years ago — _onionesque · 2026-10-16
- JevAgentHarness: a 4B decision model lets cheap agents offload tool choices from the LLM — youjiaxuan · 2026-10-16
- Google-led paper uses sequential auctions to organize decentralized LLM agent workflows — _onionesque · 2026-10-16