tree-verification

The paper introduces SPOT, a 0.62M-parameter drafter that predicts token commit order for diffusion language models, enabling lossless tree-based speculative decoding with coupled-noise match verification that cuts target passes by up to 6.8x and boosts throughput up to 3.2x across six DLMs.

This paper introduces Weaver, a lightweight autoregressive adapter that constructs proposal trees from factorized drafters' top-K marginals, achieving a 4.37x speedup over autoregressive decoding and outperforming the DFlash baseline by 24.7%.