publications

2026

1. arXiv

   Latent-Augmented Discrete Diffusion Models (LADD)

   Dario Shariatian, Alain Durmus, and Stefano Peluchetti

   arXiv preprint, Jan 2026

   Abs Bib

   We augment the masking process of diffusion language models with continuous latent embeddings, enabling cross-token modeling and improving few-step generation.

   @article{shariatian2026ladd,
     title = {Latent-Augmented Discrete Diffusion Models (LADD)},
     author = {Shariatian, Dario and Durmus, Alain and Peluchetti, Stefano},
     journal = {arXiv preprint},
     year = {2026},
     month = jan
   }

2025

1. NeurIPS

   Algorithm and Data Dependent Generalization Bounds for Score-Based Generative Models

   Dario Shariatian, Benjamin Dupuis, Maxime Haddouche, and 2 more authors

   In Advances in Neural Information Processing Systems, Sep 2025

   Abs arXiv Bib Code

   We establish generalization bounds for diffusion models that account jointly for optimization dynamics and data distribution, together with supporting empirical results.

   @inproceedings{shariatian2025generalization,
     title = {Algorithm and Data Dependent Generalization Bounds for Score-Based Generative Models},
     author = {Shariatian, Dario and Dupuis, Benjamin and Haddouche, Maxime and Durmus, Alain and Simsekli, Umut},
     booktitle = {Advances in Neural Information Processing Systems},
     year = {2025},
     month = sep,
   }

2. ICML

   Bit-Level Discrete Diffusion with Markov Probabilistic Models: An Improved Framework with Sharp Convergence Bounds under Minimal Assumptions

   Dario Shariatian, Le-Tuyet-Nhi Pham, Antonio Ocello, and 2 more authors

   In International Conference on Machine Learning, Feb 2025

   Abs arXiv Bib Code

   We develop a discrete diffusion method for bit data that outperforms MD4 and Discrete Flow Matching on binarized MNIST while using about 2.5x fewer network evaluations, with supporting theoretical analysis.

   @inproceedings{shariatian2025dmpm,
     title = {Bit-Level Discrete Diffusion with Markov Probabilistic Models: An Improved Framework with Sharp Convergence Bounds under Minimal Assumptions},
     author = {Shariatian, Dario and Pham, Le-Tuyet-Nhi and Ocello, Antonio and Conforti, Giovanni and Durmus, Alain},
     booktitle = {International Conference on Machine Learning},
     year = {2025},
     month = feb,
   }

3. ICLR

   Heavy-Tailed Diffusion with Denoising Levy Probabilistic Models

   Dario Shariatian, Umut Simsekli, and Alain Durmus

   In International Conference on Learning Representations, Jan 2025

   Abs arXiv Bib Code Slides

   We develop a diffusion-model framework for better modeling heavy-tailed and imbalanced data.

   @inproceedings{shariatian2025dlpm,
     title = {Heavy-Tailed Diffusion with Denoising Levy Probabilistic Models},
     author = {Shariatian, Dario and Simsekli, Umut and Durmus, Alain},
     booktitle = {International Conference on Learning Representations},
     year = {2025},
     month = jan,
   }

2024

1. NeurIPS

   Piecewise Deterministic Generative Models

   Andrea Bertazzi, Dario Shariatian, Umut Simsekli, and 2 more authors

   In Advances in Neural Information Processing Systems, Jul 2024

   Abs arXiv Bib Code

   We introduce a class of generative models based on piecewise-deterministic Markov processes, combining deterministic motion with random jumps, and report promising empirical results.

   @inproceedings{bertazzi2024pdmp,
     title = {Piecewise Deterministic Generative Models},
     author = {Bertazzi, Andrea and Shariatian, Dario and Simsekli, Umut and Moulines, {\'E}ric and Durmus, Alain},
     booktitle = {Advances in Neural Information Processing Systems},
     year = {2024},
     month = jul,
   }