New speculative decoding methods accelerate LLM inference

Multiple new papers propose adaptive draft pruning, cost-aware MoE decoding, memory-augmented speculation, and tree-based parallel drafting to speed up LLM inference. One method, D-cut, reduces verification depth for batched speculative decoding.