3 papers
cs.LG2026
Search-Augmented Masked Diffusion Models for Constrained Generation
Huu Binh Ta, Michael Cardei, Alvaro Velasquez +1
Discrete diffusion models generate sequences by iteratively denoising samples corrupted by categorical noise, offering an appealing alternative to autoregressive decoding for struc…
cs.LG2025
Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation
Jacob K. Christopher, Michael Cardei, Jinhao Liang +1
Despite the remarkable generative capabilities of diffusion models, their integration into safety-critical or scientifically rigorous applications remains hindered by the need to e…
cs.CL2025
Constrained Discrete Diffusion
Michael Cardei, Jacob K Christopher, Thomas Hartvigsen +2
Discrete diffusion models are a class of generative models that construct sequences by progressively denoising samples from a categorical noise distribution. Beyond their rapidly g…