Interactive NeurIPS tutorial teaches speculative decoding: draft model proposes, target model verifies
Madisonkanna · x · 2026-09-07
dizhangfdu and Madisonkanna built an interactive tutorial on speculative decoding for the NeurIPS Education Track, with an accompanying blog post. It explains why autoregressive decoding is the inference bottleneck, how a small draft model proposes several tokens that the target model verifies, and why strict rejection sampling keeps outputs losslessly aligned with the target distribution. Speculative decoding now runs under nearly every hosted LLM, and the tutorial traces its evolution and what's next.
More from Infra
- BaseQuant V1 quants for agentic Qwen3.8-27B hit 17-34% lower KL than Unsloth — nightowlsleeping · 2026-10-23
- PhD students in some countries get B200s on demand, unlike their US peers — HildeKuehne · 2026-10-23
- Nvidia's Berlin GTC spotlights humanoid robots and Vera Rubin AI supercomputing — emmanuelvivier · 2026-10-23
- Lenovo adds 5 AI Library use cases, claims 1-week deployment and up to 70% lower token cost — shashib · 2026-10-23
- Your kernel doesn't need to beat cuBLAS on every shape, argues GPU dev — blelbach · 2026-10-23
- llama.cpp team launches Llama: one-click local AI on your Mac menu bar — Hugging Face · 2026-10-23