Author

Wei Guo

Georgia Institute of Technology

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#artificial intelligence May 2026

Continuous Diffusion Scales Competitively with Discrete Diffusion for Language

The first scaling law for continuous DLMs that rivals discrete DLMs is established: RePlaid exhibits a compute gap of only $20\times$ compared to autoregressive models, outperforms Duo while using fewer parameters, and outperforms MDLM in the over-trained regime.

Zhi-Han Yang, Wei Guo, Shuibai Zhang et al. · arXiv.org · 12 citations · ⚡2

#machine learning Preprint Aug 2026

Scaling Reinforcement Learning for Diffusion Models via Velocity Matching

This work proposes reward-based velocity matching (RVM), a simple trajectory-free update that acts directly on the velocity field and provides a general framework that recovers recent fine-tuning methods, including RAM and DiffusionNFT, as special cases.

Jaemoo Choi, Wei Guo, Yuchen Zhu et al. · 1 citation