streamingllm-82661e2b·1 events·first seen Aliases: StreamingLLM
A new arXiv preprint introduces Windowed-MTP, a training-free modification to Multi-Token-Prediction draft heads used in speculative decoding that applies a StreamingLLM-style sliding window with attention sinks to the draft's attention only. At 1M-token context, the method drops ~99% of draft KV cache entries while leaving the full-attention verifier intact, making the approach lossless by construction. Evaluated on Qwen GDN-MoE 35B/122B and a Mamba2-hybrid 120B in SGLang, it reduces per-decode-step cost by 28–44% over the native MTP draft baseline. The fix addresses a compounding problem where deep native draft heads can become net-negative at long contexts, especially under hybrid/linear-attention targets.