Interactive tutorial: how speculative decoding evolved, and when it stays lossless
kalyan_kpl · x · 2026-09-07
An interactive tutorial by Lily Zhang and Madison Kanna (under review, NeurIPS 2026 Education Track) covers speculative decoding: why autoregressive decoding bottlenecks inference, how draft-model-plus-verification speeds it up losslessly (output distribution preserved), the method's evolution since 2023, and diffusion-style parallel drafting as a next step. A must-read for AI/ML engineers working on LLM inference.
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