Nannan Wu

Autoregressive DNA language models generate left to right, yet genome repair and editing usually condition on both flanks. The CreatiPhage team converted a 144.5M-parameter phage autoregressive model into CPDD, a 147.5M-parameter bidirectional discrete diffusion model; on 522 screened phage coding sequences it restores randomly masked bases more accurately than the comparable diffusion model PhaGen, and in a mixed-corruption test a single forward pass returns 42.4% of visible incorrect bases to the correct base.

Autoregressive DNA language models generate left to right, yet genome repair and editing usually condition on both flanks. The CreatiPhage team converted a 144.5M-parameter phage autoregressive model into CPDD, a 147.5M-parameter bidirectional discrete diffusion model; on 522 screened phage coding sequences it restores randomly masked bases more accurately than the comparable diffusion model PhaGen, and in a mixed-corruption test a single forward pass returns 42.4% of visible incorrect bases to the correct base.

EvSpark is a speculative decoding system for hybrid convolutional-recurrent-attention DNA foundation models such as Evo2: it verifies draft blocks in parallel and restores all three classes of inference state by selecting retained intermediate states without replay, reaching 2.96x on 43 real-sequence prompts and 3.27x including five synthetic controls on an Evo2 7B 48-prompt benchmark with three training seeds, retaining 1.84x-2.43x at 262k context, and yielding 2.18x-2.46x on real sequences and 2.51x-2.78x on the full suite for 20B and 40B targets.

EvSpark is a speculative decoding system for hybrid convolutional-recurrent-attention DNA foundation models such as Evo2: it verifies draft blocks in parallel and restores all three classes of inference state by selecting retained intermediate states without replay, reaching 2.96x on 43 real-sequence prompts and 3.27x including five synthetic controls on an Evo2 7B 48-prompt benchmark with three training seeds, retaining 1.84x-2.43x at 262k context, and yielding 2.18x-2.46x on real sequences and 2.51x-2.78x on the full suite for 20B and 40B targets.