A derivation-, tensor-, training-, and runtime-level comparison of draft models, retrieval and prompt lookup, self-speculation, dependent draft heads, multi-candidate exact sampling, token-tree construction, and hardware-aware tree optimization.
A tensor- and runtime-level study of EAGLE feature autoregression, shifted-token conditioning, draft training, dynamic trees, HASS context alignment, and the EAGLE-3 design transition.
A mechanism-oriented study note on Medusa decoding heads, same-model candidate generation, candidate trees, tree attention masks, typical acceptance, Medusa-1, Medusa-2, and branch KV state.