angelspec-f9744956·1 events·first seen Aliases: AngelSpec
AngelSpec is a new training framework that unifies autoregressive multi-token prediction (MTP) and block-parallel speculative decoding, co-specializing each drafter to different data domains (conversational vs. code/math). The paper introduces DFly, a block-diffusion architecture with hybrid target-conditioning and adaptive verification depth that treats verification as a shared batch-level resource. On the Hy3-A21B model, DFly achieves 1.98–2.40x speedup over autoregressive decoding and 10.5–11.8% higher throughput than DFlash across concurrency levels from 4 to 64. The framework and code are released publicly.