infrastructure
Stable Tokens Stopped Paying for More Denoising
CAI-DLLM uses first-step confidence to commit easy tokens and reserve later denoising for harder ones.
Summary
CAI-DLLM uses first-step confidence to commit easy tokens and reserve later denoising for harder ones.
The training-free method reports up to 18.2-times wall-clock speedup on LLaDA GSM8K and 13.1-times on Dream HumanEval with slightly higher measured accuracy in those settings. On harder tasks speedups reached 44.8 times with a largest 4.4-point accuracy drop, exposing the quality boundary.
Why it matters
CAI-DLLM uses first-step confidence to commit easy tokens and reserve later denoising for harder ones.
Limits and context
No additional limitation was separately recorded.
Key claims
CAI-DLLM uses first-step confidence to commit easy tokens and reserve later denoising for harder ones.
Evidence: source-2026-08-25-013
Sources
- arXiv preprint 2608.22646arXiv · primary research
Corrections
No corrections have been recorded for this story.