# Research

All papers

## 2025

1. [Mercury: Ultra-Fast Language Models Based on Diffusion](https://arxiv.org/abs/2506.17298)  
   *Samar Khanna, Siddhant Kharbanda, Shufan Li, Harshit Varma, Eric Wang, Sawyer Birnbaum, Ziyang Luo, Yanis Miraoui, Akash Palrecha, Stefano Ermon, Aditya Grover*  
   June 17, 2025

2. [LaViDa: A Large Diffusion Language Model for Multimodal Understanding](https://arxiv.org/abs/2505.16839)  
   *Shufan Li, Konstantinos Kallidromitis, Hritik Bansal, Akash Gokul, Yusuke Kato, Kazuki Kozuka, Jason Kuen, Zhe Lin, Kai-Wei Chang, Aditya Grover*  
   May 22, 2025

3. [d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning](https://arxiv.org/abs/2504.12216)  
   *Siyan Zhao, Devaansh Gupta, Qinqing Zheng, Aditya Grover*  
   April 16, 2025

4. [Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models](https://arxiv.org/abs/2503.09573)  
   *Marianne Arriola, Aaron Gokaslan, Justin T. Chiu, Zhihan Yang, Zhixuan Qi, Jiaqi Han, Subham Sekhar Sahoo, Volodymyr Kuleshov*  
   March 12, 2025

5. [Remasking Discrete Diffusion Models with Inference-Time Scaling](https://arxiv.org/abs/2503.00307)  
   *Guanghan Wang, Yair Schiff, Subham Sekhar Sahoo, Volodymyr Kuleshov*  
   March 1, 2025

## 2024

1. [Simple Guidance Mechanisms for Discrete Diffusion Models](https://arxiv.org/html/2412.10193v1)  
   *Yair Schiff, Subham Sekhar Sahoo, Guanghan Wang, Hao Phung, Alexander Rush, Volodymyr Kuleshov*  
   December 13, 2024

2. [Simple and Effective Masked Diffusion Language Models](https://arxiv.org/pdf/2406.07524)  
   *Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, Aaron Gokaslan, Edgar Marroquin, Justin T Chiu, Alexander Rush, Volodymyr Kuleshov*  
   November 10, 2024

## 2023

1. [Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution](https://arxiv.org/abs/2310.16834)  
   *Aaron Lou, Chenlin Meng, Stefano Ermon*  
   October 25, 2023

## 2020

1. [Score-Based Generative Modeling through Stochastic Differential Equations](https://arxiv.org/abs/2011.13456)  
   *Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole*  
   November 26, 2020

## 2019

1. [Generative Modeling by Estimating Gradients of the Data Distribution](https://arxiv.org/abs/1907.05600)  
   *Yang Song, Stefano Ermon*  
   July 12, 2019

The future of LLMs is here.