denoiser

GDSD proposes a reinforcement learning method that directly distills denoisers from advantage-guided self-teachers for diffusion language models, avoiding biases from ELBO-based likelihood surrogates. It achieves up to +19.6% accuracy improvements on planning, math, and coding benchmarks over prior state-of-the-art methods.